Methods and Systems for Adjusting Power Consumption based on a Fixed-Duration Power Option Agreement

ABSTRACT

Examples relate to adjusting load power consumption based on a power option agreement. A computing system may receive power option data that is based on a power option agreement and specify minimum power thresholds associated with time intervals. The computing system may determine a performance strategy for a load (e.g., set of computing systems) based on a combination of the power option data and one or more monitored conditions. The performance strategy may specify a power consumption target for the load for each time interval such that each power consumption target is equal to or greater than the minimum power threshold associated with each time interval. The computing system may provide instructions the set of computing systems to perform one or more computational operations based on the performance strategy.

The present application is a continuation of U.S. patent applicationSer. No. 16/702,931, filed on Dec. 4, 2019, the entire contents of whichare herein incorporated by reference.

FIELD

This specification relates to power consumption adjustments when usinggrid power and/or intermittent behind-the-meter power.

BACKGROUND

“Electrical grid” or “grid,” as used herein, refers to a Wide AreaSynchronous Grid (also known as an Interconnection), and is a regionalscale or greater electric power grid that that operates at asynchronized frequency and is electrically tied together during normalsystem conditions. An electrical grid delivers electricity fromgeneration stations to consumers. An electrical grid includes: (i)generation stations that produce electrical power at large scales fordelivery through the grid, (ii) high voltage transmission lines thatcarry that power from the generation stations to demand centers, and(iii) distribution networks carry that power to individual customers.

FIG. 1 illustrates a typical electrical grid, such as a North AmericanInterconnection or the synchronous grid of Continental Europe (formerlyknown as the UCTE grid). The electrical grid of FIG. 1 can be describedwith respect to the various segments that make up the grid.

A generation segment 102 includes one or more generation stations thatproduce utility-scale electricity (typically >50 MW), such as a nuclearplant 102 a, a coal plant 102 b, a wind power station (i.e., wind farm)102 c, and/or a photovoltaic power station (i.e., a solar farm) 102 d.Generation stations are differentiated from building-mounted and otherdecentralized or local wind or solar power applications because theysupply power at the utility level and scale (>50 MW), rather than to alocal user or users. The primary purpose of generation stations is toproduce power for distribution through the grid, and in exchange forpayment for the supplied electricity. Each of the generation stations102 a-d includes power generation equipment 102 e-h, respectively,typically capable of supply utility-scale power (>50 MW). For example,the power generation equipment 102 g at wind power station 102 cincludes wind turbines, and the power generation equipment 102 h atphotovoltaic power station 102 d includes photovoltaic panels.

Each of the generation stations 102 a-d may further include stationelectrical equipment 102 i-1 respectively. Station electrical equipment102 i-1 are each illustrated in FIG. 1 as distinct elements forsimplified illustrative purposes only and may, alternatively oradditionally, be distributed throughout the power generation equipment,102 e-h, respectively. For example, at wind power station 102 c, eachwind turbine may include transformers, frequency converters, powerconverters, and/or electrical filters. Energy generated at each windturbine may be collected by distribution lines along strings of windturbines and move through collectors, switches, transformers, frequencyconverters, power converters, electrical filters, and/or other stationelectrical equipment before leaving the wind power station 102 c.Similarly, at photovoltaic power station 102 d, individual photovoltaicpanels and/or arrays of photovoltaic panels may include inverters,transformers, frequency converters, power converters, and/or electricalfilters. Energy generated at each photovoltaic panel and/or array may becollected by distribution lines along the photovoltaic panels and movethrough collectors, switches, transformers, frequency converters, powerconverters, electrical filters, and/or other station electricalequipment before leaving the photovoltaic power station 102 d.

Each generation station 102 a-d may produce AC or DC electrical currentwhich is then typically stepped up to a higher AC voltage before leavingthe respective generation station. For example, wind turbines maytypically produce AC electrical energy at 600V to 700V, which may thenbe stepped up to 34.5 kV before leaving the generation station 102 d. Insome cases, the voltage may be stepped up multiple times and to adifferent voltage before exiting the generation station 102 c. Asanother example, photovoltaic arrays may produce DC voltage at 600V to900V, which is then inverted to AC voltage and may be stepped up to 34.5kV before leaving the generation station 102 d. In some cases, thevoltage may be stepped up multiple times and to a different voltagebefore exiting the generation station 102 d.

Upon exiting the generation segment 102, electrical power generated atgeneration stations 102 a-d passes through a respective Point ofInterconnection (“POI”) 103 between a generation station (e.g., 102 a-d)and the rest of the grid. A respective POI 103 represents the point ofconnection between a generation station's (e.g. 102 a-d) equipment and atransmission system (e.g., transmission segment 104) associated withelectrical grid. In some cases, at the POI 103, generated power fromgeneration stations 102 a-d may be stepped up at transformer systems 103e-h to high voltage scales suitable for long-distance transmission alongtransmission lines 104 a. Typically, the generated electrical energyleaving the POI 103 will be at 115 kV AC or above, but in some cases itmay be as low as, for example, 69 kV for shorter distance transmissionsalong transmission lines 104 a. Each of transformer systems 103 e-h maybe a single transformer or may be multiple transformers operating inparallel or series and may be co-located or located in geographicallydistinct locations. Each of the transformer systems 103 e-h may includesubstations and other links between the generation stations 102 a-d andthe transmission lines 104 a.

A key aspect of the POI 103 is that this is where generation-sidemetering occurs. One or more utility-scale generation-side meters 103a-d (e.g., settlement meters) are located at settlement metering pointsat the respective POI 103 for each generation station 102 a-d. Theutility-scale generation-side meters 103 a-d measure power supplied fromgeneration stations 102 a-d into the transmission segment 104 foreventual distribution throughout the grid.

For electricity consumption, the price consumers pay for powerdistributed through electric power grids is typically composed of, amongother costs, Generation, Administration, and Transmission & Distribution(“T&D”) costs. T&D costs represent a significant portion of the overallprice paid by consumers for electricity. These costs include capitalcosts (land, equipment, substations, wire, etc.), costs associated withelectrical transmission losses, and operation and maintenance costs.

For utility-scale electricity supply, operators of generation stations(e.g., 102 a-d) are paid a variable market price for the amount of powerthe operator generates and provides to the grid, which is typicallydetermined via a power purchase agreement (PPA) between the generationstation operator and a grid operator. The amount of power the generationstation operator generates and provides to the grid is measured byutility-scale generation-side meters (e.g., 103 a-d) at settlementmetering points. As illustrated in FIG. 1, the utility-scalegeneration-side meters 103 a-d are shown on a low side of thetransformer systems 103 e-h), but they may alternatively be locatedwithin the transformer systems 103 e-h or on the high side of thetransformer systems 103 e-h. A key aspect of a utility-scalegeneration-side meter is that it is able to meter the power suppliedfrom a specific generation station into the grid. As a result, the gridoperator can use that information to calculate and process payments forpower supplied from the generation station to the grid. That price paidfor the power supplied from the generation station is then subject toT&D costs, as well as other costs, in order to determine the price paidby consumers.

After passing through the utility-scale generation-side meters in thePOI 103, the power originally generated at the generation stations 102a-d is transmitted onto and along the transmission lines 104 a in thetransmission segment 104. Typically, the electrical energy istransmitted as AC at 115 kV+ or above, though it may be as low as 69 kVfor short transmission distances. In some cases, the transmissionsegment 104 may include further power conversions to aid in efficiencyor stability. For example, transmission segment 104 may includehigh-voltage DC (“HVDC”) portions (along with conversion equipment) toaid in frequency synchronization across portions of the transmissionsegment 104. As another example, transmission segment 104 may includetransformers to step AC voltage up and then back down to aid in longdistance transmission (e.g., 230 kV, 500 kV, 765 kV, etc.).

Power generated at the generation stations 104 a-d is ultimatelydestined for use by consumers connected to the grid. Once the energy hasbeen transmitted along the transmission segment 104, the voltage will bestepped down by transformer systems 105 a-c in the step down segment 105so that it can move into the distribution segment 106.

In the distribution segment 106, distribution networks 106 a-c takepower that has been stepped down from the transmission lines 104 a anddistribute it to local customers, such as local sub-grids (illustratedat 106 a), industrial customers, including large EV charging networks(illustrated at 106 b), and/or residential and retail customers,including individual EV charging stations (illustrated at 106 c).Customer meters 106 d, 106 f measure the power used by each of thegrid-connected customers in distribution networks 106 a-c. Customermeters 106 d are typically load meters that are unidirectional andmeasure power use. Some of the local customers in the distributionnetworks 106 a-d may have local wind or solar power systems 106 e ownedby the customer. As discussed above, these local customer power systems106 e are decentralized and supply power directly to the customer(s).Customers with decentralized wind or solar power systems 106 e may havecustomer meters 106 f that are bidirectional or net-metering meters thatcan track when the local customer power systems 106 e produce power inexcess of the customer's use, thereby allowing the utility to provide acredit to the customer's monthly electricity bill. Customer meters 106d, 106 f differ from utility-scale generation-side meters (e.g.,settlement meters) in at least the following characteristics: design(electro-mechanical or electronic vs current transformer), scale(typically less than 1600 amps vs. typically greater than 50 MW;typically less than 600V vs. typically greater than 14 kV), primaryfunction (use vs. supply metering), economic purpose (credit against usevs payment for power), and location (in a distribution network at pointof use vs. at a settlement metering point at a Point of Interconnectionbetween a generation station and a transmission line).

To maintain stability of the grid, the grid operator strives to maintaina balance between the amount of power entering the grid from generationstations (e.g., 102 a-d) and the amount of grid power used by loads(e.g., customers in the distribution segment 106). In order to maintaingrid stability and manage congestion, grid operators may take steps toreduce the supply of power arriving from generation stations (e.g., 102a-d) when necessary (e.g., curtailment). Particularly, grid operatorsmay decrease the market price paid for generated power todis-incentivize generation stations (e.g., 102 a-d) from generating andsupplying power to the grid. In some cases, the market price may even gonegative such that generation station operators must pay for power theyallow into the grid. In addition, some situations may arise where gridoperators explicitly direct a generation station (e.g., 102 a-d) toreduce or stop the amount of power the station is supplying to the grid.

Power market fluctuations, power system conditions (e.g., power factorfluctuation or generation station startup and testing), and operationaldirectives resulting in reduced or discontinued generation all can havedisparate effects on renewal energy generators and can occur multipletimes in a day and last for indeterminate periods of time. Curtailment,in particular, is particularly problematic.

According to the National Renewable Energy Laboratory's Technical ReportTP-6A20-60983 (March 2014):

-   -   [C]urtailment [is] a reduction in the output of a generator from        what it could otherwise produce given available resources (e.g.,        wind or sunlight), typically on an involuntary basis.        Curtailments can result when operators or utilities command wind        and solar generators to reduce output to minimize transmission        congestion or otherwise manage the system or achieve the optimal        mix of resources. Curtailment of wind and solar resources        typically occurs because of transmission congestion or lack of        transmission access, but it can also occur for reasons such as        excess generation during low load periods that could cause        baseload generators to reach minimum generation thresholds,        because of voltage or interconnection issues, or to maintain        frequency requirements, particularly for small, isolated grids.        Curtailment is one among many tools to maintain system energy        balance, which can also include grid capacity, hydropower and        thermal generation, demand response, storage, and institutional        changes. Deciding which method to use is primarily a matter of        economics and operational practice.    -   “Curtailment” today does not necessarily mean what it did in the        early 2000s. Two separate changes in the electric sector have        shaped curtailment practices since that time: the utility-scale        deployment of wind power, which has no fuel cost, and the        evolution of wholesale power markets. These simultaneous changes        have led to new operational challenges but have also expanded        the array of market-based tools for addressing them.    -   Practices vary significantly by region and market design. In        places with centrally-organized wholesale power markets and        experience with wind power, manual wind energy curtailment        processes are increasingly being replaced by transparent        offer-based market mechanisms that base dispatch on economics.        Market protocols that dispatch generation based on economics can        also result in renewable energy plants generating less than what        they could potentially produce with available wind or sunlight.        This is often referred to by grid operators by other terms, such        as “downward dispatch.” In places served primarily by vertically        integrated utilities, power purchase agreements (PPAs) between        the utility and the wind developer increasingly contain        financial provisions for curtailment contingencies.    -   Some reductions in output are determined by how a wind operator        values dispatch versus non-dispatch. Other curtailments of wind        are determined by the grid operator in response to potential        reliability events. Still other curtailments result from        overdevelopment of wind power in transmission-constrained areas.    -   Dispatch below maximum output (curtailment) can be more of an        issue for wind and solar generators than it is for fossil        generation units because of differences in their cost        structures. The economics of wind and solar generation depend on        the ability to generate electricity whenever there is sufficient        sunlight or wind to power their facilities.    -   Because wind and solar generators have substantial capital costs        but no fuel costs (i.e., minimal variable costs), maximizing        output improves their ability to recover capital costs. In        contrast, fossil generators have higher variable costs, such as        fuel costs. Avoiding these costs can, depending on the economics        of a specific generator, to some degree reduce the financial        impact of curtailment, especially if the generator's capital        costs are included in a utility's rate base.

Curtailment may result in available energy being wasted because solarand wind operators have zero variable cost (which may not be true to thesame extent for fossil generation units which can simply reduce theamount of fuel that is being used). With wind generation, in particular,it may also take some time for a wind farm to become fully operationalfollowing curtailment. As such, until the time that the wind farm isfully operational, the wind farm may not be operating with optimumefficiency and/or may not be able to provide power to the grid.

SUMMARY

In an example, a system includes a set of computing systems. The set ofcomputing systems is configured to perform computational operationsusing power from a power grid. The system also includes a control systemconfigured to monitor a set of conditions and, while monitoring the setof conditions, receive first power option data based, at least in part,on a power option agreement. The first power option data specify a firstminimum power threshold associated with a first time interval. Thecontrol system is further configured to provide first controlinstructions for the set of computing systems based on a combination ofat least a portion of the first power option data and at least onecondition of the set of conditions responsive to receiving the firstpower option data. The first control instructions comprises a firstpower consumption target for the set of computing systems for the firsttime interval, and the first power consumption target is equal to orgreater than the first minimum power threshold associated with the firsttime interval. The control system is also configured to, whilemonitoring the set of conditions, receive second power option databased, at least in part, on the power option agreement. The second poweroption data specify a second minimum power threshold associated with asecond time interval. Responsive to receiving the second power optiondata, the control system is configured to provide second controlinstructions for the set of computing systems based on a combination ofat least a portion of the second power data and at least one conditionof the set of conditions. The second control instructions comprises asecond power consumption target for the set of computing systems for thesecond time interval, and wherein the second power consumption target isequal to or greater than the second minimum power threshold associatedwith the second time interval.

In another example, a method involves monitoring, at a computing system,a set of conditions, and while monitoring the set of conditions,receiving first power option data based, at least in part, on a poweroption agreement. The first power option data specify a first minimumpower threshold associated with a first time interval. The methodfurther involves, responsive to receiving the first power option data,providing first control instructions for a set of computing systemsbased on a combination of at least a portion of the first power optiondata and at least one condition of the set of conditions. The firstcontrol instructions comprises a first power consumption target for theset of computing systems for the first time interval, and the firstpower consumption target is equal to or greater than the first minimumpower threshold associated with the first time interval. The methodfurther involves, while monitoring the set of conditions, receivingsecond power option data based, at least in part, on the power optionagreement. The second power option data specify a second minimum powerthreshold associated with a second time interval. The method alsoinvolves, responsive to receiving the second power option data,providing second control instructions for the set of computing systemsbased on a combination of at least a portion of the second power dataand at least one condition of the set of conditions. The second controlinstructions comprises a second power consumption target for the set ofcomputing systems for the second time interval, and the second powerconsumption target is equal to or greater than the second minimum powerthreshold associated with the second time interval.

In yet another example, a system is provided. The system includes a setof computing systems, where the set of computing systems is configuredto perform computational operations using power from a power grid. Thesystem also includes a control system configured to monitor a set ofconditions and receive power option data based, at least in part, on apower option agreement. The power option data specify: (i) a set ofminimum power thresholds, and (ii) a set of time intervals, where eachminimum power threshold in the set of minimum power thresholds isassociated with a time interval in the set of time intervals. Thecontrol system is further configured to, responsive to receiving thepower option data, determine a performance strategy for the set ofcomputing systems based on a combination of at least a portion of thepower option data and at least one condition in the set of conditions.The performance strategy comprises a power consumption target for theset of computing systems for each time interval in the set of timeintervals, where each power consumption target is equal to or greaterthan the minimum power threshold associated with each time interval. Thecontrol system is also configured to provide instructions to the set ofcomputing systems to perform one or more computational operations basedon the performance strategy.

In a further example, non-transitory computer-readable medium isdescribed that is configured to store instructions, that when executedby a computing system, causes the computing system to perform operationsconsistent with the method steps described above.

Other aspects of the present invention will be apparent from thefollowing description and claims.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a typical electrical grid.

FIG. 2 shows a behind-the-meter arrangement with optional grid power,including one or more flexible datacenters, according to one or moreexample embodiments.

FIG. 3 shows a block diagram of a remote master control system,according to one or more example embodiments.

FIG. 4 a block diagram of a generation station, according to one or moreexample embodiments.

FIG. 5 shows a block diagram of a flexible datacenter, according to oneor more example embodiments.

FIG. 6A shows a structural arrangement of a flexible datacenter,according to one or more example embodiments.

FIG. 6B shows a set of computing systems arranged in a straightconfiguration, according to one or more example embodiments.

FIG. 7 shows a control distribution system for a flexible datacenter,according to one or more example embodiments.

FIG. 8 shows a control distribution system for a fleet of flexibledatacenters, according to one or more example embodiments.

FIG. 9 shows a queue distribution system for a traditional datacenterand a flexible datacenter, according to one or more example embodiments.

FIG. 10A shows a method of dynamic power consumption at a flexibledatacenter using behind-the-meter power, according to one or moreexample embodiments.

FIG. 10B shows a method of dynamic power delivery at a flexibledatacenter using behind-the-meter power, according to one or moreexample embodiments.

FIG. 11 shows a block diagram of a system for implementing powerconsumption adjustments based on a power option agreement, according toone or more embodiments.

FIG. 12 shows a graph representing power option data based on a poweroption agreement, according to one or more embodiments.

FIG. 13 shows a method for implementing power consumption adjustmentsbased on a fixed-duration power option agreement, according to one ormore embodiments.

FIG. 14 shows a method for implementing power consumption adjustmentsbased on a dynamic power option agreement, according to one or moreembodiments.

DETAILED DESCRIPTION

Disclosed examples will now be described more fully hereinafter withreference to the accompanying drawings, in which some, but not all ofthe disclosed examples are shown. Different examples may be describedand should not be construed as limited to the examples set forth herein.

As discussed above, the market price paid to generation stations forsupplying power to the grid often fluctuates due to various factors,including the need to maintain grid stability and based on currentdemand and usage by connected loads in distribution networks. Due tothese factors, situations can arise where generation stations areoffered substantially lower prices to deter an over-supply of power tothe grid. Although these situations typically exist temporarily,generation stations are sometimes forced to either sell power to thegrid at the much lower prices or adjust operations to decrease theamount of power generated. Furthermore, some situations may even requiregeneration stations to incur costs in order to offload power to the gridor to shut down generation temporarily.

The volatility in the market price offered for power supplied to thegrid can be especially problematic for some types of generationstations. In particular, wind farms and some other types of renewableresource power producers may lack the ability to quickly adjustoperations in response to changes in the market price offered forsupplying power to the grid. As a result, power generation andmanagement at some generation stations can be inefficient, which canfrequently result in power being sold to the grid at low or negativeprices. In some situations, a generation station may even opt to haltpower generation temporarily to avoid such unfavorable pricing. As such,the time required to halt and to restart the power generation at ageneration station can reduce the generation station's ability to takeadvantage of rising market prices for power supplied to the grid.

Example embodiments provided herein aim to assist generation stations inmanaging power generation operations and avoid unfavorable power pricingsituations like those described above. In particular, exampleembodiments may involve providing a load that is positionedbehind-the-meter (“BTM”) and enabling the load to utilize power receivedbehind-the-meter at a generation station in a timely manner. As ageneral rule of thumb, BTM power is not subject to traditional T&Dcosts.

For purposes herein, a generation station is considered to be configuredfor the primary purpose of generating utility-scale power for supply tothe electrical grid (e.g., a Wide Area Synchronous Grid or a NorthAmerican Interconnect).

In one embodiment, equipment located behind-the-meter (“BTM equipment”)is equipment that is electrically connected to a generation station'spower generation equipment behind (i.e., prior to) the generationstation's POI with an electrical grid.

In one embodiment, behind-the-meter power (“BTM power”) is electricalpower produced by a generation station's power generation equipment andutilized behind (i.e., prior to) the generation station's POI with anelectrical grid.

In another embodiment, equipment may be considered behind-the-meter ifit is electrically connected to a generation station that is subject tometering by a utility-scale generation-side meter (e.g., settlementmeter), and the BTM equipment receives power from the generationstation, but the power received by the BTM equipment from the generationstation has not passed through the utility-scale generation-side meter.In one embodiment, the utility-scale generation-side meter for thegeneration station is located at the generation station's POI. Inanother embodiment, the utility-scale generation-side meter for thegeneration station is at a location other than the POI for thegeneration station—for example, a substation between the generationstation and the generation station's POI.

In another embodiment, power may be considered behind-the-meter if it iselectrical power produced at a generation station that is subject tometering by a utility-scale generation-side meter (e.g., settlementmeter), and the BTM power is utilized before being metered at theutility-scale generation-side meter. In one embodiment, theutility-scale generation-side meter for the generation station islocated at the generation station's POI. In another embodiment, theutility-scale generation-side meter for the generation station is at alocation other than the POI for the generation station—for example, asubstation between the generation station and the generation station'sPOI.

In another embodiment, equipment may be considered behind-the-meter ifit is electrically connected to a generation station that supplies powerto a grid, and the BTM equipment receives power from the generationstation that is not subject to T&D charges, but power received from thegrid that is supplied by the generation station is subject to T&Dcharges.

In another embodiment, power may be considered behind-the-meter if it iselectrical power produced at a generation station that supplies power toa grid, and the BTM power is not subject to T&D charges before beingused by electrical equipment, but power received from the grid that issupplied by the generation station is subject to T&D charges.

In another embodiment, equipment may be considered behind-the-meter ifthe BTM equipment receives power generated from the generation stationand that received power is not routed through the electrical grid beforebeing delivered to the BTM equipment.

In another embodiment, power may be considered behind-the-meter if it iselectrical power produced at a generation station, and BTM equipmentreceives that generated power, and that generated power received by theBTM equipment is not routed through the electrical grid before beingdelivered to the BTM equipment.

For purposes herein, BTM equipment may also be referred to as abehind-the-meter load (“BTM load”) when the BTM equipment is activelyconsuming BTM power.

Beneficially, where BTM power is not subject to traditional T&D costs, awind farm or other type of generation station can be connected to BTMloads which can allow the generation station to selectively avoid theadverse or less-than optimal cost structure occasionally associated withsupplying power to the grid by shunting generated power to the BTM load.

An arrangement that positions and connects a BTM load to a generationstation can offer several advantages. In such arrangements, thegeneration station may selectively choose whether to supply power to thegrid or to the BTM load, or both. The operator of a BTM load may pay toutilize BTM power at a cost less than that charged through a consumermeter (e.g., 106 d, 106 f) located at a distribution network (e.g., 106a-c) receiving power from the grid. The operator of a BTM load mayadditionally or alternatively charge less than the market rate toconsume excess power generated at the generation station duringcurtailment. As a result, the generation station may direct generatedpower based on the “best” price that the generation station can receiveduring a given time frame, and/or the lowest cost the generation stationmay incur from negative market pricing during curtailment. The “best”price may be the highest price that the generation station may receivefor its generated power during a given duration, but can also differwithin embodiments and may depend on various factors, such as a priorPPA.

In one example, by having a behind-the-meter option available, ageneration station may transition from supplying all generated power tothe grid to supplying some or all generated power to one or more BTMloads when the market price paid for power by grid operators drops belowa predefined threshold (e.g., the price that the operator of the BTMload is willing to pay the generation station for power). Thus, byhaving an alternative option for power consumption (i.e., one or moreBTM loads), the generation station can selectively utilize the differentoptions to maximize the price received for generated power. In addition,the generation station may also utilize a BTM load to avoid or reducethe economic impact in situations when supplying power to the grid wouldresult in the generation station incurring a net cost.

Providing BTM power to a load can also benefit the BTM load operator. ABTM load may be able to receive and utilize BTM power received from thegeneration station at a cost that is lower than the cost for power fromthe grid (e.g., at a customer meter 106 d, 106 f). This is primarily dueto the avoidance (or significant reduction) in T&D costs and the marketeffects of curtailment. As indicated above, the generation station maybe willing to divert generated power to the BTM load rather thansupplying the grid due to changing market conditions, or duringmaintenance periods, or for other non-market conditions. Thus, somesituations may arise where the generation station offers power to theBTM load at a price that is substantially lower than the price availableon the grid. Furthermore, in some situations, the BTM load may even beable to obtain and utilize BTM power from a generation station at nocost or even at negative pricing since the generation station may rathersupply the BTM load with generated power during a given time rangeinstead of paying a higher price for the grid to take the power ormodifying operations to decrease power output.

Another example of cost-effective use of BTM power is when thegeneration station 202 is selling power to the grid at a negative pricethat is offset by a production tax credit. In certain circumstances, thevalue of the production tax credit may exceed the price the generationstation 202 would have to pay to the grid power to offload generation'sstation 202 generated power. Advantageously, one or more flexibledatacenters 220 may take the generated power behind-the-meter, therebyallowing the generation station 202 to produce and obtain the productiontax credit, while selling less power to the grid at the negative price.

Another example of cost-effective behind-the-meter power is when thegeneration station 202 is selling power to the grid at a negative pricebecause the grid is oversupplied and/or the generation station 202 isinstructed to stand down and stop producing altogether. A grid operatormay select and direct certain generation stations to go offline and stopsupplying power to the grid. Advantageously, one or more flexibledatacenters may be used to take power behind-the-meter, thereby allowingthe generation station 202 to stop supplying power to the grid, butstill stay online and make productive use of the power generated.

Another example of beneficial behind-the-meter power use is when thegeneration station 202 is producing power that is, with reference to thegrid, unstable, out of phase, or at the wrong frequency, or the grid isalready unstable, out of phase, or at the wrong frequency. A gridoperator may select certain generation stations to go either offline andstop producing power, or to take corrective action with respect to thegrid power stability, phase, or frequency. Advantageously, one or moreflexible datacenters 220 may be used to selectively consume powerbehind-the-meter, thereby allowing the generation station 202 to stopproviding power to the grid and/or provide corrective feedback to thegrid.

Another example of beneficial behind-the-meter power use is thatcost-effective behind-the-meter power availability may occur when thegeneration station 202 is starting up or testing. Individual equipmentin the power generation equipment 210 may be routinely offline forinstallation, maintenance, and/or service and the individual units mustbe tested prior to coming online as part of overall power generationequipment 210. During such testing or maintenance time, one or moreflexible datacenters may be intermittently powered by the one or moreunits of the power generation equipment 210 that are offline from theoverall power generation equipment 210.

Another example of beneficial behind-the-meter power use is thatdatacenter control systems at the flexible datacenters 220 may quicklyramp up and ramp down power consumption by computing systems in theflexible datacenters 220 based on power availability from the generationstation 202. For instance, if the grid requires additional power andsignals the demand via a higher local price for power, the generationstation 202 can supply the grid with power nearly instantly by havingactive flexible datacenters 220 quickly ramp down and turn off computingsystems (or switch to a stored energy source), thereby reducing anactive BTM load.

Another example of beneficial behind-the-meter power use is in newphotovoltaic generation stations 202. For example, it is common todesign and build new photovoltaic generation stations with a surplus ofpower capacity to account for degradation in efficiency of thephotovoltaic panels over the life of the generation stations. Excesspower availability at the generation station can occur when there isexcess local power generation and/or low grid demand. In high incidentsunlight situations, a photovoltaic generation station 202 may generatemore power than the intended capacity of generation station 202. In suchsituations, a photovoltaic generation station 202 may have to take stepsto protect its equipment from damage, which may include taking one ormore photovoltaic panels offline or shunting their voltage to dummyloads or the ground. Advantageously, one or more flexible datacenters(e.g., the flexible datacenters 220) may take power behind-the-meter atthe Generations Station 202, thereby allowing the generation station 202to operate the power generation equipment 210 within operating rangeswhile the flexible datacenters 220 receive BTM power withouttransmission or distribution costs.

Thus, for at least the reasons described herein, arrangements thatinvolves providing a BTM load as an alternative option for a generationstation to direct its generated power to can serve as a mutuallybeneficial relationship in which both the generation station and the BTMload can economically benefit. The above-noted examples of beneficialuse of BTM power are merely exemplary and are not intended to limit thescope of what one of ordinary skill in the art would recognize asbenefits to unutilized BTM power capacity, BTM power pricing, or BTMpower consumption.

Within example embodiments described herein, various types ofutility-scale power producers may operate as generation stations 202that are capable of supplying power to one or more loadsbehind-the-meter. For instance, renewable energy sources (e.g., wind,solar, hydroelectric, wave, water current, tidal), fossil fuel powergeneration sources (coal, natural gas), and other types of powerproducers (e.g., nuclear power) may be positioned in an arrangement thatenables the intermittent supply of generated power behind-the-meter toone or more BTM loads. One of ordinary skill in the art will recognizethat the generation station 202 may vary based on an application ordesign in accordance with one or more example embodiments.

In addition, the particular arrangement (e.g., connections) between thegeneration station and one or more BTM loads can vary within examples.In one embodiment, a generation station may be positioned in anarrangement wherein the generation station selectively supplies power tothe grid and/or to one or more BTM loads. As such, power cost-analysisand other factors (e.g., predicted weather conditions, contractualobligations, etc.) may be used by the generation station, a BTM loadcontrol system, a remote master control system, or some other system orenterprise, to selectively output power to either the grid or to one ormore BTM loads in a manner that maximizes revenue to the generationstation. In such an arrangement, the generation station may also be ableto supply both the grid and one or more BTM loads simultaneously. Insome instances, the arrangement may be configured to allow dynamicmanipulation of the percentage of the overall generated power that issupplied to each option at a given time. For example, in some timeperiods, the generation station may supply no power to the BTM load.

In addition, the type of loads that are positioned behind-the-meter canvary within example embodiments. In general, a load that isbehind-the-meter may correspond to any type of load capable of receivingand utilizing power behind-the-meter from a generation station. Someexamples of loads include, but are not limited to, datacenters andelectric vehicle (EV) charging stations.

Preferred BTM loads are loads that can be subject to intermittent powersupply because BTM power may be available intermittently. In someinstances, the generation station may generate power intermittently. Forexample, wind power station 102 c and/or photovoltaic power station 102d may only generate power when resource are available or favorable.Additionally or alternatively, BTM power availability at a generationstation may only be available intermittently due to power marketfluctuations, power system conditions (e.g., power factor fluctuation orgeneration station startup and testing), and/or operational directivesfrom grid operators or generation station operators.

Some example embodiments of BTM loads described herein involve using oneor more computing systems to serve as a BTM load at a generationstation. In particular, the computing system or computing systems mayreceive power behind-the-meter from the generation station to performvarious computational operations, such as processing or storinginformation, performing calculations, mining for cryptocurrencies,supporting blockchain ledgers, and/or executing applications, etc.

Multiple computing systems positioned behind-the-meter may operate aspart of a “flexible” datacenter that is configured to operate onlyintermittently and to receive and utilize BTM power to carry out variouscomputational operations similar to a traditional datacenter. Inparticular, the flexible datacenter may include computing systems andother components (e.g., support infrastructure, a control system)configured to utilize BTM power from one or more generation stations.The flexible datacenter may be configured to use particular load rampingabilities (e.g., quickly increase or decrease power usage) toeffectively operate during intermittent periods of time when power isavailable from a generation station and supplied to the flexibledatacenter behind-the-meter, such as during situations when supplyinggenerated power to the grid is not favorable for the generation station.

In some instances, the amount of power consumed by the computing systemsat a flexible datacenter can be ramped up and down quickly, andpotentially with high granularity (i.e., the load can be changed insmall increments if desired). This may be done based on monitored powersystem conditions or other information analyses as discussed herein. Asrecited above, this can enable a generation station to avoid negativepower market pricing and to respond quickly to grid directives. And byextension, the flexible datacenter may obtain BTM power at a price lowerthan the cost for power from the grid.

Various types of computing systems can provide granular power ramping.Preferably, the computing systems can perform computational tasks thatare immune to, or not substantially hindered by, frequent interruptionsor slow-downs in processing as the computing systems ramp down or up. Insome embodiments, a control system may be used to activate orde-activate one or more computing systems in an array of computingsystems. For example, the control system may provide controlinstructions to one or more blockchain miners (e.g., a group ofblockchain miners), including instructions for powering on or off,adjusting frequency of computing systems performing operations (e.g.,adjusting the processing frequency), adjusting the quantity ofoperations being performed, and when to operate within a low power mode(if available).

Within examples, a control system may correspond to a specializedcomputing system or may be a computing system within a datacenterserving in the role of the control system. The location of the controlsystem can vary within examples as well. For instance, the controlsystem may be located at a datacenter or physically separate from thedatacenter. In some examples, the control system may be part of anetwork of control systems that manage computational operations, powerconsumption, and other aspects of a fleet of datacenters. The fleet ofdatacenters may include one or more traditional datacenters and/orflexible datacenters.

Some embodiments may involve using one or more control systems to directtime-insensitive (e.g., interruptible) computational tasks tocomputational hardware, such as central processing units (CPUs) andgraphics processing units (GPUs), sited behind the meter, while otherhardware is sited in front of the meter (i.e., consuming metered gridpower via a customer meter (e.g., 106 d, 106 f) and possibly remote fromthe behind-the-meter hardware. As such, parallel computing processes,such as Monte Carlo simulations, batch processing of financialtransactions, graphics rendering, machine learning, neural networkprocessing, queued operations, and oil and gas field simulation models,are good candidates for such interruptible computational operations.

FIG. 2 shows a behind-the-meter arrangement with optional grid-power,including one or more flexible datacenters, according to one or moreexample embodiments. Dark arrows illustrate a typical power deliverydirection. Consistent with FIG. 1, the arrangement illustrates ageneration station 202 in the generation segment 102 of a Wide-AreaSynchronous Grid. The generation station 202 supplies utility-scalepower (typically >50 MW) via a generation power connection 250 to thePoint of Interconnection 103 between the generation station 202 and therest of the grid. Typically, the power supplied on connection 250 may beat 34.5 kV AC, but it may be higher or lower. Depending on the voltageat connection 250 and the voltage at transmission lines 104 a, atransformer system 203 may step up the power supplied from thegeneration station 202 to high voltage (e.g., 115 kV+AC) fortransmission over connection 252 and onto transmission lines 104 a oftransmission segment 104. Grid power carried on the transmission segment104 may be from generation station 202 as well as other generationstations (not shown). Also consistent with FIG. 1, grid power isconsumed at one or more distribution networks, including exampledistribution network 206. Grid power may be taken from the transmissionlines 104 a via connector 254 and stepped down to distribution networkvoltages (e.g., typically 4 kV to 26 kV AC) and sent into thedistribution networks, such as distribution network 206 via distributionline 256. The power on distribution line 256 may be further stepped down(not shown) before entering individual consumer facilities such as aremote master control system 262 and/or traditional datacenters 260 viacustomer meters 206A, which may correspond to customer meters 106 d inFIG. 1, or customer meters 106 f in FIG. 1 if the respective consumerfacility includes a local customer power system, such as 106 e (notshown in FIG. 2).

Consistent with FIG. 1, power entering the grid from generation station202 is metered by a utility-scale generation-side meter. A utility-scalegeneration-side meter 253 is shown on the low side of transformer system203 and an alternative location is shown as 253A on the high side oftransformer system 203. Both locations may be considered settlementmetering points for the generation station 202 at the POI 103.Alternatively, a utility-scale generation-side meter for the generationstation 202 may be located at another location consistent with thedescriptions of such meters provided herein.

Generation station 202 includes power generation equipment 210, whichmay include, as examples, wind turbines and/or photovoltaic panels.Power generation equipment 210 may further include other electricalequipment, including but not limited to switches, busses, collectors,inverters, and power unit transformers (e.g., transformers in windturbines).

As illustrated in FIG. 2, generation station 202 is configured toconnect with BTM equipment which may function as BTM loads. In theillustrated embodiment of FIG. 2, the BTM equipment includes flexibledatacenters 220. Various configurations to supply BTM power to flexibledatacenters 220 within the arrangement of FIG. 2 are described herein.

In one configuration, generated power may travel from the powergeneration equipment 210 over one or more connectors 230A, 230B to oneor more electrical busses 240A, 240B, respectively. Each of theconnectors 230A, 230B may be a switched connector such that power may berouted independently to 240A and/or 240B. For illustrative purposesonly, connector 230B is shown with an open switch, and connector 230A isshown with a closed switch, but either or both may be reversed in someembodiments. Aspects of this configuration can be used in variousembodiments when BTM power is supplied without significant powerconversion to BTM loads.

In various configurations, the busses 240A and 240B may be separated byan open switch 240C or combined into a common bus by a closed switch240C.

In another configuration, generated power may travel from the powergeneration equipment 210 to the high side of a local step-downtransformer 214. The generated power may then travel from the low sideof the local step-down transformer 214 over one or more connectors 232A,232B to the one or more electrical busses 240A, 240B, respectively. Eachof the connectors 232A, 232B may be a switched connector such that powermay be routed independently to 240A and/or 240B. For illustrativepurposes only, connector 232A is shown with an open switch, andconnector 232B is shown with a closed switch, but either or both may bereversed in some embodiments. Aspects of this configuration can be usedwhen it is preferable to connect BTM power to the power generationequipment 210, but the generated power must be stepped down prior to useat the BTM loads.

In another configuration, generated power may travel from the powergeneration equipment 210 to the low side of a local step-up transformer212. The generated power may then travel from the high side of the localstep-up transformer 212 over one or more connectors 234A, 234B to theone or more electrical busses 240A, 240B, respectively. Each of theconnectors 234A, 234B may be a switched connector such that power may berouted independently to 240A and/or 240B. For illustrative purposesonly, both connectors 234A, 234B are shown with open switches, buteither or both may be closed in some embodiments. Aspects of thisconfiguration can be used when it is preferable to connect BTM power tothe outbound connector 250 or the high side of the local step-uptransformer 212.

In another configuration, generated power may travel from the powergeneration equipment 210 to the low side of the local step-uptransformer 212. The generated power may then travel from the high sideof the local step-up transformer 212 to the high side of local step-downtransformer 213. The generated power may then travel from the low sideof the local step-down transformer 213 over one or more connectors 236A,236B to the one or more electrical busses 240A, 240B, respectively. Eachof the connectors 236A, 2346 may be a switched connector such that powermay be routed independently to 240A and/or 240B. For illustrativepurposes only, both connectors 236A, 236B are shown with open switches,but either or both may be closed in some embodiments. Aspects of thisconfiguration can be used when it is preferable to connect BTM power tothe outbound connector 250 or the high side of the local step-uptransformer 212, but the power must be stepped down prior to use at theBTM loads.

In one embodiment, power generated at the generation station 202 may beused to power a generation station control system 216 located at thegeneration station 202, when power is available. The generation stationcontrol system 216 may typically control the operation of the generationstation 202. Generated power used at the generation station controlsystem 216 may be supplied from bus 240A via connector 216A and/or frombus 240B via connector 216B. Each of the connectors 216A, 216B may be aswitched connector such that power may be routed independently to 240Aand/or 240B. While the generation station control system 216 can consumeBTM power when powered via bus 240A or bus 240B, the BTM power taken bygeneration station control system 216 is insignificant in terms ofrendering an economic benefit. Further, the generation station controlsystem 216 is not configured to operate intermittently, as it generallymust remain always on. Further still, the generation station controlsystem 216 does not have the ability to quickly ramp a BTM load up ordown.

In another embodiment, grid power may alternatively or additionally beused to power the generation station control system 216. As illustratedhere, metered grid power from a distribution network, such asdistribution network 206 for simplicity of illustration purposes only,may be used to power generation station control system 216 overconnector 216C. Connector 216C may be a switched connector so thatmetered grid power to the generation station control system 216 can beswitched on or off as needed. More commonly, metered grid power would bedelivered to the generation station control system 216 via a separatedistribution network (not shown), and also over a switched connector.Any such grid power delivered to the generation station control system216 is metered by a customer meter 206A and subject to T&D costs.

In another embodiment, when power generation equipment 210 is in an idleor off state and not generating power, grid power may backfeed intogeneration station 202 through POI 103 and such grid power may power thegeneration station control system 216.

In some configurations, an energy storage system 218 may be connected tothe generation station 202 via connector 218A, which may be a switchedconnector. For illustrative purposes only, connector 218A is shown withan open switch but in some embodiments it may be closed. The energystorage system 218 may be connected to bus 240A and/or bus 240B andstore energy produced by the power generation equipment 210. The energystorage system may also be isolated from generation station 202 byswitch 242A. In times of need, such as when the power generationequipment in an idle or off state and not generating power, the energystorage system may feed power to, for example, the flexible datacenters220. The energy storage system may also be isolated from the flexibledatacenters 220 by switch 242B.

In a preferred embodiment, as illustrated, power generation equipment210 supplies BTM power via connector 242 to flexible datacenters 220.The BTM power used by the flexible datacenters 220 was generated by thegeneration station 202 and did not pass through the POI 103 orutility-scale generation-side meter 253, and is not subject to T&Dcharges. Power received at the flexible datacenters 220 may be receivedthrough respective power input connectors 220A. Each of the respectiveconnectors 220A may be switched connector that can electrically isolatethe respective flexible datacenter 220 from the connector 242. Powerequipment 220B may be arranged between the flexible datacenters 220 andthe connector 242. The power equipment 220B may include, but is notlimited to, power conditioners, unit transformers, inverters, andisolation equipment. As illustrated, each flexible datacenter 220 may beserved by a respective power equipment 220B. However, in anotherembodiment, one power equipment 220B may serve multiple flexibledatacenter 220.

In one embodiment, flexible datacenters 220 may be considered BTMequipment located behind-the-meter and electrically connected to thepower generation equipment 210 behind (i.e., prior to) the generationstation's POI 103 with the rest of the electrical grid.

In one embodiment, BTM power produced by the power generation equipment210 is utilized by the flexible datacenters 220 behind (i.e., prior to)the generation station's POI with an electrical grid.

In another embodiment, flexible datacenters 220 may be considered BTMequipment located behind-the-meter as the flexible datacenters 220 areelectrically connected to the generation station 202, and generationstation 202 is subject to metering by utility-scale generation-sidemeter 253 (or 253A, or another utility-scale generation-side meter), andthe flexible datacenters 220 receive power from the generation station202, but the power received by the flexible datacenters 220 from thegeneration station 202 has not passed through a utility-scalegeneration-side meter. In this embodiment, the utility-scalegeneration-side meter 253 (or 253A) for the generation station 202 islocated at the generation station's 202 POI 103. In another embodiment,the utility-scale generation-side meter for the generation station 202is at a location other than the POI for the generation station 202—forexample, a substation (not shown) between the generation station 202 andthe generation station's POI 103.

In another embodiment, power from the generation station 202 is suppliedto the flexible datacenters 220 as BTM power, where power produced atthe generation station 202 is subject to metering by utility-scalegeneration-side meter 253 (or 253A, or another utility-scalegeneration-side meter), but the BTM power supplied to the flexibledatacenters 220 is utilized before being metered at the utility-scalegeneration-side meter 253 (or 253A, or another utility-scalegeneration-side meter). In this embodiment, the utility-scalegeneration-side meter 253 (or 253A) for the generation station 202 islocated at the generation station's 202 POI 103. In another embodiment,the utility-scale generation-side meter for the generation station 202is at a location other than the POI for the generation station 202—forexample, a substation (not shown) between the generation station 202 andthe generation station's POI 103.

In another embodiment, flexible datacenters 220 may be considered BTMequipment located behind-the-meter as they are electrically connected tothe generation station 202 that supplies power to the grid, and theflexible datacenters 220 receive power from the generation station 202that is not subject to T&D charges, but power otherwise received fromthe grid that is supplied by the generation station 202 is subject toT&D charges.

In another embodiment, power from the generation station 202 is suppliedto the flexible datacenters 220 as BTM power, where electrical power isgenerated at the generation station 202 that supplies power to a grid,and the generated power is not subject to T&D charges before being usedby flexible datacenters 220, but power otherwise received from theconnected grid is subject to T&D charges.

In another embodiment, flexible datacenters 220 may be considered BTMequipment located behind-the-meter because they receive power generatedfrom the generation station 202 intended for the grid, and that receivedpower is not routed through the electrical grid before being deliveredto the flexible datacenters 220.

In another embodiment, power from the generation station 202 is suppliedto the flexible datacenters 220 as BTM power, where electrical power isgenerated at the generation station 202 for distribution to the grid,and the flexible datacenters 220 receive that power, and that receivedpower is not routed through the electrical grid before being deliveredto the flexible datacenters 220.

In another embodiment, metered grid power may alternatively oradditionally be used to power one or more of the flexible datacenters220, or a portion within one or more of the flexible datacenters 220. Asillustrated here for simplicity, metered grid power from a distributionnetwork, such as distribution network 206, may be used to power one ormore flexible datacenters 220 over connector 256A and/or 256B. Each ofconnector 256A and/or 256B may be a switched connector so that meteredgrid power to the flexible datacenters 220 can be switched on or off asneeded. More commonly, metered grid power would be delivered to theflexible datacenters 220 via a separate distribution network (notshown), and also over switched connectors. Any such grid power deliveredto the flexible datacenters 220 is metered by customer meters 206A andsubject to T&D costs. In one embodiment, connector 256B may supplymetered grid power to a portion of one or more flexible datacenters 220.For example, connector 256B may supply metered grid power to controland/or communication systems for the flexible datacenters 220 that needconstant power and cannot be subject to intermittent BTM power.Connector 242 may supply solely BTM power from the generation station202 to high power demand computing systems within the flexibledatacenters 220, in which case at least a portion of each flexibledatacenters 220 so connected is operating as a BTM load. In anotherembodiment, connector 256A and/or 256B may supply all power used at oneor more of the flexible datacenters 220, in which case each of theflexible datacenters 220 so connected would not be operating as a BTMload.

In another embodiment, when power generation equipment 210 is in an idleor off state and not generating power, grid power may backfeed intogeneration station 202 through POI 103 and such grid power may power theflexible datacenters 220.

The flexible datacenters 220 are shown in an example arrangementrelative to the generation station 202. Particularly, generated powerfrom the generation station 202 may be supplied to the flexibledatacenters 220 through a series of connectors and/or busses (e.g.,232B, 240B, 242, 220A). As illustrated, in other embodiments, connectorsbetween the power generation equipment 210 and other components may beswitched open or closed, allowing other pathways for power transferbetween the power generation equipment 210 and components, including theflexible datacenters 220. Additionally, the connector arrangement shownis illustrative only and other circuit arrangements are contemplatedwithin the scope of supplying BTM power to a BTM load at generationstation 202. For example, there may be more or fewer transformers, orone or more of transformers 212, 213, 214 may be transformer systemswith multiple steppings and/or may include additional power equipmentincluding but not limited to power conditioners, filters, switches,inverters, and/or AC/DC-DC/AC isolators. As another example, meteredgrid power connections to flexible datacenters 220 are shown via both256A and 256B; however, a single connection may connect one or moreflexible datacenters 220 (or power equipment 220B) to metered grid powerand the one or more flexible datacenters 220 (or power equipment 220B)may include switching apparatus to direct BTM power and/or metered gridpower to control systems, communication systems, and/or computingsystems as desired.

In some examples, BTM power may arrive at the flexible datacenters 220in a three-phase AC format. As such, power equipment (e.g., powerequipment 220B) at one or more of the flexible datacenters 220 mayenable each flexible datacenter 220 to use one or more phases of thepower. For instance, the flexible datacenters 220 may utilize powerequipment (e.g., power equipment 220B, or alternatively or additionallypower equipment that is part of the flexible datacenter 220) to convertBTM power received from the generation station 202 for use at computingsystems at each flexible datacenter 220. In other examples, the BTMpower may arrive at one or more of the flexible datacenters 220 as DCpower. As such, the flexible datacenters 220 may use the DC power topower computing systems. In some such examples, the DC power may berouted through a DC-to-DC converter that is part of power equipment 220Band/or flexibles datacenter 220.

In some configurations, a flexible datacenter 220 may be arranged toonly have access to power received behind-the-meter from a generationstation 202. In the arrangement of FIG. 2, the flexible datacenters 220may be arranged only with a connection to the generation station 202 anddepend solely on power received behind-the-meter from the generationstation 202. Alternatively or additionally, the flexible datacenters 220may receive power from energy storage system 218.

In some configurations, one or more of the flexible datacenters 220 canbe arranged to have connections to multiple sources that are capable ofsupplying power to a flexible datacenter 220. To illustrate a firstexample, the flexible datacenters 220 are shown connected to connector242, which can be connected or disconnected via switches to the energystorage system 218 via connector 218A, the generation station 202 viabus 240B, and grid power via metered connector 256A. In one embodiment,the flexible datacenters 220 may selectively use power receivedbehind-the-meter from the generation station 202, stored power suppliedby the energy storage system 218, and/or grid power. For instance,flexible datacenters 220 may use power stored in the energy storagesystem 218 when costs for using power supplied behind-the-meter from thegeneration station 202 are disadvantageous. By having access to theenergy storage system 218 available, the flexible datacenters 220 mayuse the stored power and allow the generation station 202 tosubsequently refill the energy storage system 218 when cost for powerbehind-the-meter is low. Alternatively, the flexible datacenters 220 mayuse power from multiple sources simultaneously to power differentcomponents (e.g., a first set and a second set of computing systems).Thus, the flexible datacenters 220 may leverage the multiple connectionsin a manner that can reduce the cost for power used by the computingsystems at the flexible datacenters 220. The flexible datacenters 220control system or the remote master control system 262 may monitor powerconditions and other factors to determine whether the flexibledatacenters 220 should use power from either the generation station 202,grid power, the energy storage system 218, none of the sources, or asubset of sources during a given time range. Other arrangements arepossible as well. For example, the arrangement of FIG. 2 illustrateseach flexible datacenter 220 as connected via a single connector 242 toenergy storage system 218, generation station 202, and metered gridpower via 256A. However, one or more flexible datacenters 220 may haveindependent switched connections to each energy source, allowing the oneor more flexible datacenters 220 to operate from different energysources than other flexible datacenters 220 at the same time.

The selection of which power source to use at a flexible datacenter(e.g., the flexible datacenters 220) or another type of BTM load canchange based on various factors, such as the cost and availability ofpower from both sources, the type of computing systems using the powerat the flexible datacenters 220 (e.g., some systems may require areliable source of power for a long period), the nature of thecomputational operations being performed at the flexible datacenters 220(e.g., a high priority task may require immediate completion regardlessof cost), and temperature and weather conditions, among other possiblefactors. As such, a datacenter control system at the flexibledatacenters 220, the remote master control system 262, or another entity(e.g., an operator at the generation station 202) may also influenceand/or determine the source of power that the flexible datacenters 220use at a given time to complete computational operations.

In some example embodiments, the flexible datacenters 220 may use powerfrom the different sources to serve different purposes. For example, theflexible datacenters 220 may use metered power from grid power to powerone or more systems at the flexible datacenters 220 that are configuredto be always-on (or almost always on), such as a control and/orcommunication system and/or one or more computing systems (e.g., a setof computing systems performing highly important computationaloperations). The flexible datacenters 220 may use BTM power to powerother components within the flexible datacenters 220, such as one ormore computing systems that perform less critical computationaloperations.

In some examples, one or more flexible datacenters 220 may be deployedat the generation station 202. In other examples, flexible datacenters220 may be deployed at a location geographically remote from thegeneration station 202, while still maintaining a BTM power connectionto the generation station 202.

In another example arrangement, the generation station 202 may beconnected to a first BTM load (e.g., a flexible datacenter 220) and maysupply power to additional BTM loads via connections between the firstBTM load and the additional BTM loads (e.g., a connection between aflexible datacenter 220 and another flexible datacenter 220).

The arrangement in FIG. 2, and components included therein, are fornon-limiting illustration purposes and other arrangements arecontemplated in examples. For instance, in another example embodiment,the arrangement of FIG. 2 may include more or fewer components, such asmore BTM loads, different connections between power sources and loads,and/or a different number of datacenters. In addition, some examples mayinvolve one or more components within the arrangement of FIG. 2 beingcombined or further divided.

Within the arrangement of FIG. 2, a control system, such as the remotemaster control system 262 or another component (e.g., a control systemassociated with the grid operator, the generation station control system216, or a datacenter control system associated with a traditionaldatacenter or one or more flexible datacenters) may use information toefficiently manage various operations of some of the components withinthe arrangement of FIG. 2. For example, the remote master control system262 or another component may manage distribution and execution ofcomputational operations at one or more traditional datacenters 260and/or flexible datacenters 220 via one or more information-processingalgorithms. These algorithms may utilize past and current information inreal-time to manage operations of the different components. Thesealgorithms may also make some predictions based on past trends andinformation analysis. In some examples, multiple computing systems mayoperate as a network to process information.

Information used to make decisions may include economic and/orpower-related information, such as monitored power system conditions.Monitored power system conditions may include one or more of excesspower generation at a generation station 202, excess power at ageneration station 202 that a connected grid cannot receive, powergeneration at a generation station 202 subject to economic curtailment,power generation at a generation station 202 subject to reliabilitycurtailment, power generation at a generation station 202 subject topower factor correction, low power generation at a generation station202, start up conditions at a generation station 202, transient powergeneration conditions at a generation station 202, or testing conditionswhere there is an economic advantage to using behind-the-meter powergeneration at a generation station 202. These different monitored powersystem conditions can be weighted differently during processing andanalysis.

In some examples, the information can include the cost for power fromavailable sources (e.g., BTM power at the generation station 202 versusmetered grid power) to enable comparisons to be made which power sourcecosts less. In some instances, the information may include historicprices for power to enable the remote master control system 262 oranother system to predict potential future prices in similar situations(e.g., the cost of power tends to trend upwards for grid power duringwarmer weather and peak-use hours). The information may also indicatethe availability of power from the various sources (e.g., BTM power atthe generation station 262, the energy storage system 218 at thegeneration station 262, and/or metered grid power).

In addition, the information may also include other data, includinginformation associated with operations at components within thearrangement. For instance, the information may include data associatedwith performance of operations at the flexible datacenters 220 and thetraditional datacenters 260, such as the number of computational taskscurrently being performed, the types of tasks being performed (e.g.,type of computational operation, time-sensitivity, etc.), the number,types, and capabilities of available computing systems, the amount ofcomputational tasks awaiting performance, and the types of computingsystems at one or more datacenters, among others. The information mayalso include data specifying the conditions at one or more datacenters(e.g., whether or not the temperatures are in a desired range, theamount of power available within an energy storage system such as 218),the amount of computational tasks awaiting performance in the queue ofone or more of the datacenters, and the identities of the entitiesassociated with the computational operations at one or more of thedatacenters. Entities associated with computational operations may be,for example, owners of the datacenters, customers who purchasecomputational time at the datacenters, or other entities.

The information used by the remote master control system 262 or anothercomponent may include data associated with the computational operationsto be performed, such as deadlines, priorities (e.g., high vs. lowpriority tasks), cost to perform based on required computing systems,the optimal computing systems (e.g., CPU vs GPU vs ASIC; processing unitcapabilities, speeds, or frequencies, or instructional sets executableby the processing units) for performing each requested computationaltask, and prices each entity (e.g., company) is willing to pay forcomputational operations to be performed or otherwise supported viacomputing systems at a traditional datacenter 260 or a flexibledatacenter 220, among others. In addition, the information may alsoinclude other data (e.g., weather conditions at locations of datacentersor power sources, any emergencies associated with a datacenter or powersource, or the current value of bids associated with an auction forcomputational tasks).

The information may be updated in-real time and used to make thedifferent operational decisions within the arrangement of FIG. 2. Forinstance, the information may help a component (e.g., the remote mastercontrol system 262 or a control system at a flexible datacenter 220)determine when to ramp up or ramp down power use at a flexibledatacenter 220 or when to switch one or more computing systems at aflexible datacenter 220 into a low power mode or to operate at adifferent frequency, among other operational adjustments. Theinformation can additionally or alternatively help a component withinthe arrangement of FIG. 2 to determine when to transfer computationaloperations between computing systems or between datacenters based onvarious factors. In some instances, the information may also be used todetermine when to temporarily stop performing a computational operationor when to perform a computational operation at multiple sites forredundancy or other reasons. The information may further be used todetermine when to accept new computational operations from entities orwhen to temporarily suspend accepting new tasks to be performed due tolack of computing system availability.

The remote master control system 262 represents a computing system thatis capable of obtaining, managing, and using the information describedabove to manage and oversee one or more operations within thearrangement of FIG. 2. As such, the remote master control system 262 maybe one or more computing systems configured to process all, or a subsetof, the information described above, such as power, environment,computational characterization, and economic factors to assist with thedistribution and execution of computing operations among one or moredatacenters. For instance, the remote master control system 262 may beconfigured to obtain and delegate computational operations among one ormore datacenters based on a weighted analysis of a variety of factors,including one or more of the cost and availability of power, the typesand availability of the computing systems at each datacenter, currentand predicted weather conditions at the different locations of flexibledatacenters (e.g., flexible datacenters 220) and generation stations(e.g., generation stations 202), levels of power storage available atone or more energy storage systems (e.g., energy storage system 218),and deadlines and other attributes associated with particularcomputational operations, among other possible factors. As such, theanalysis of information performed by the remote master control system262 may vary within examples. For instance, the remote master controlsystem 262 may use real-time information to determine whether or not toroute a computational operation to a particular flexible datacenter(e.g., a flexible datacenter 220) or to transition a computationaloperation between datacenters (e.g., from traditional datacenter 260 toa flexible datacenter 220).

As shown in FIG. 2, the generation station 202 may be able to supplypower to the grid and/or BTM loads such as flexible datacenters 220.With such a configuration, the generation station 202 may selectivelyprovide power to the BTM loads and/or the grid based on economic andpower availability considerations. For example, the generation station202 may supply power to the grid when the price paid for the powerexceeds a particular threshold (e.g., the power price offered byoperators of the flexible datacenters 220). In some instances, theoperator of a flexible datacenter and the operator of a generationstation capable of supplying BTM power to the flexible datacenter mayutilize a predefined arrangement (e.g., a contract) that specifies aduration and/or price range when the generation station may supply powerto the flexible datacenter.

The remote master control system 262 may be capable of directing one ormore flexible datacenters 220 to ramp-up or ramp-down to desired powerconsumption levels, and/or to control cooperative action of multipleflexible datacenters by determining how to power each individualflexible datacenter 220 in accordance with operational directives.

The configuration of the remote master control system 262 can varywithin examples as further discussed with respect to FIGS. 2, 3, and7-9. The remote master control system 262 may operate as a singlecomputing system or may involve a network of computing systems.Preferably, the remote master control system 262 is implemented acrossone or more servers in a fault-tolerant operating environment thatensures continuous uptime and connectivity by virtue of its distributednature. Alternatively, although the remote master control system 262 isshown as a physically separate component arrangement for FIG. 2, theremote master control system 262 may be combined with another componentin other embodiments. To illustrate an example, the remote mastercontrol system 262 may operate as part of a flexible datacenter (e.g., acomputing system or a datacenter control system of the flexibledatacenter 220), including sharing components with a flexibledatacenter, sharing power with a flexible datacenter, and/or beingco-located with a flexible datacenter.

In addition, the remote master control system 262 may communicate withcomponents within the arrangement of FIG. 2 using various communicationtechnologies, including wired and wireless communication technologies.For instance, the remote master control system 262 may use wired (notillustrated) or wireless communication to communicate with datacentercontrol systems or other computing systems at the flexible datacenters220 and the traditional datacenters 260. The remote master controlsystem 262 may also communicate with entities inside or outside thearrangement of FIG. 2 and other components within the arrangement ofFIG. 2 via wired or wireless communication. For instance, the remotemaster control system 262 may use wireless communication to obtaincomputational operations from entities seeking support for thecomputational operations at one or more datacenters in exchange forpayment. The remote master control system 262 may communicate directlywith the entities or may obtain the computational operations from thetraditional datacenters 260. For instance, an entity may submit jobs(e.g., computational operations) to one or more traditional datacenters260. The remote master control system 262 may determine thattransferring one or more of the computational operations to a flexibledatacenter 220 may better support the transferred computationaloperations. For example, the remote master control system 262 maydetermine that the transfer may enable the computational operations tobe completed quicker and/or at a lower cost. In some examples, theremote master control system 262 may communicate with the entity toobtain approval prior to transferring the one or more computationaloperations.

The remote master control system 262 may also communicate with gridoperators and/or an operator of generation station 202 to help determinepower management strategies when distributing computational operationsacross the various datacenters. In addition, the remote master controlsystem 262 may communicate with other sources, such as weatherprediction systems, historical and current power price databases, andauction systems, etc.

In further examples, the remote master control system 262 or anothercomputing system within the arrangement of FIG. 2 may use wired orwireless communication to submit bids within an auction that involves abidder (e.g., the highest bid) obtaining computational operations orother tasks to be performed. Particularly, the remote master controlsystem 262 may use the information discussed above to develop bids toobtain computing operations for performance at available computingsystems at flexible datacenters (e.g., flexible datacenters 220).

In the example arrangement shown in FIG. 2, the flexible datacenters 220represent example loads that can receive power behind-the-meter from thegeneration station 202. In such a configuration, the flexibledatacenters 220 may obtain and utilize power behind-the-meter from thegeneration station 202 to perform various computational operations.Performance of a computational operation may involve one or morecomputing systems providing resources useful in the computationaloperation. For instance, the flexible datacenters 220 may include one ormore computing systems configured to store information, performcalculations and/or parallel processes, perform simulations, minecryptocurrencies, and execute applications, among other potential tasks.The computing systems can be specialized or generic and can be arrangedat each flexible datacenter 220 in a variety of ways (e.g., straightconfiguration, zig-zag configuration) as further discussed with respectto FIGS. 6A, 6B. Furthermore, although the example arrangementillustrated in FIG. 2 shows configurations where flexible datacenters220 serve as BTM loads, other types of loads can be used as BTM loadswithin examples.

The arrangement of FIG. 2 includes the traditional datacenters 260coupled to metered grid power. The traditional datacenters 260 usingmetered grid power to provide computational resources to supportcomputational operations. One or more enterprises may assigncomputational operations to the traditional datacenters 260 withexpectations that the datacenters reliably provide resources withoutinterruption (i.e., non-intermittently) to support the computationaloperations, such as processing abilities, networking, and/or volatilestorage. Similarly, one or more enterprises may also requestcomputational operations to be performed by the flexible datacenters220. The flexible datacenters 220 differ from the traditionaldatacenters 260 in that the flexible datacenters 220 are arranged and/orconfigured to be connected to BTM power, are expected to operateintermittently, and are expected to ramp load (and thus computationalcapability) up or down regularly in response to control directives. Insome examples, the flexible datacenters 220 and the traditionaldatacenters 260 may have similar configurations and may only differbased on the source(s) of power relied upon to power internal computingsystems. Preferably, however, the flexible datacenters 220 includeparticular fast load ramping abilities (e.g., quickly increase ordecrease power usage) and are intended and designed to effectivelyoperate during intermittent periods of time.

FIG. 3 shows a block diagram of the remote master control system 300according to one or more example embodiments. Remote master controlsystem 262 may take the form of remote master control system 300, or mayinclude less than all components in remote master control system 300,different components than in remote master control system 300, and/ormore components than in remote master control system 300.

The remote master control system 300 may perform one or more operationsdescribed herein and may include a processor 302, a data storage unit304, a communication interface 306, a user interface 308, an operationsand environment analysis module 310, and a queue system 312. In otherexamples, the remote master control system 300 may include more or fewercomponents in other possible arrangements.

As shown in FIG. 3, the various components of the remote master controlsystem 300 can be connected via one or more connection mechanisms (e.g.,a connection mechanism 314). In this disclosure, the term “connectionmechanism” means a mechanism that facilitates communication between twoor more devices, systems, components, or other entities. For instance, aconnection mechanism can be a simple mechanism, such as a cable, PCBtrace, or system bus, or a relatively complex mechanism, such as apacket-based communication network (e.g., LAN, WAN, and/or theInternet). In some instances, a connection mechanism can include anon-tangible medium (e.g., where the connection is wireless).

As part of the arrangement of FIG. 2, the remote master control system300 (corresponding to remote master control system 262) may perform avariety of operations, such as management and distribution ofcomputational operations among datacenters, monitoring operational,economic, and environment conditions, and power management. Forinstance, the remote master control system 300 may obtain computationaloperations from one or more enterprises for performance at one or moredatacenters. The remote master control system 300 may subsequently useinformation to distribute and assign the computational operations to oneor more datacenters (e.g., the flexible datacenters 220) that have theresources (e.g., particular types of computing systems and availablepower) available to complete the computational operations. In someexamples, the remote master control system 300 may assign all incomingcomputational operation requests to the queue system 312 andsubsequently assign the queued requests to computing systems based on ananalysis of current market and power conditions.

Although the remote master control system 300 is shown as a singleentity, a network of computing systems may perform the operations of theremote master control system 300 in some examples. For example, theremote master control system 300 may exist in the form of computingsystems (e.g., datacenter control systems) distributed across multipledatacenters.

The remote master control system 300 may include one or more processors302. As such, the processor 302 may represent one or moregeneral-purpose processors (e.g., a microprocessor) and/or one or morespecial-purpose processors (e.g., a digital signal processor (DSP)). Insome examples, the processor 302 may include a combination of processorswithin examples. The processor 302 may perform operations, includingprocessing data received from the other components within thearrangement of FIG. 2 and data obtained from external sources, includinginformation such as weather forecasting systems, power market pricesystems, and other types of sources or databases.

The data storage unit 304 may include one or more volatile,non-volatile, removable, and/or non-removable storage components, suchas magnetic, optical, or flash storage, and/or can be integrated inwhole or in part with the processor 302. As such, the data storage unit304 may take the form of a non-transitory computer-readable storagemedium, having stored thereon program instructions (e.g., compiled ornon-compiled program logic and/or machine code) that, when executed bythe processor 302, cause the remote master control system 300 to performone or more acts and/or functions, such as those described in thisdisclosure. Such program instructions can define and/or be part of adiscrete software application. In some instances, the remote mastercontrol system 300 can execute program instructions in response toreceiving an input, such as from the communication interface 306, theuser interface 308, or the operations and environment analysis module310. The data storage unit 304 may also store other information, such asthose types described in this disclosure.

In some examples, the data storage unit 304 may serve as storage forinformation obtained from one or more external sources. For example,data storage unit 304 may store information obtained from one or more ofthe traditional datacenters 260, a generation station 202, a systemassociated with the grid, and flexible datacenters 220. As examplesonly, data storage 304 may include, in whole or in part, local storage,dedicated server-managed storage, network attached storage, and/orcloud-based storage, and/or combinations thereof.

The communication interface 306 can allow the remote master controlsystem 300 to connect to and/or communicate with another componentaccording to one or more protocols. For instance, the communicationinterface 306 may be used to obtain information related to current,future, and past prices for power, power availability, current andpredicted weather conditions, and information regarding the differentdatacenters (e.g., current workloads at datacenters, types of computingsystems available within datacenters, price to obtain power at eachdatacenter, levels of power storage available and accessible at eachdatacenter, etc.). In an example, the communication interface 306 caninclude a wired interface, such as an Ethernet interface or ahigh-definition serial-digital-interface (HD-SDI). In another example,the communication interface 406 can include a wireless interface, suchas a cellular, satellite, WiMAX, or WI-FI interface. A connection can bea direct connection or an indirect connection, the latter being aconnection that passes through and/or traverses one or more components,such as such as a router, switcher, or other network device. Likewise, awireless transmission can be a direct transmission or an indirecttransmission. The communication interface 306 may also utilize othertypes of wireless communication to enable communication with datacenterspositioned at various locations.

The communication interface 306 may enable the remote master controlsystem 300 to communicate with the components of the arrangement of FIG.2. In addition, the communication interface 306 may also be used tocommunicate with the various datacenters, power sources, and differententerprises submitting computational operations for the datacenters tosupport.

The user interface 308 can facilitate interaction between the remotemaster control system 300 and an administrator or user, if applicable.As such, the user interface 308 can include input components such as akeyboard, a keypad, a mouse, a touch-sensitive panel, a microphone,and/or a camera, and/or output components such as a display device(which, for example, can be combined with a touch-sensitive panel), asound speaker, and/or a haptic feedback system. More generally, the userinterface 308 can include hardware and/or software components thatfacilitate interaction between remote master control system 300 and theuser of the system.

In some examples, the user interface 308 may enable the manualexamination and/or manipulation of components within the arrangement ofFIG. 2. For instance, an administrator or user may use the userinterface 308 to check the status of, or change, one or morecomputational operations, the performance or power consumption at one ormore datacenters, the number of tasks remaining within the queue system312, and other operations. As such, the user interface 308 may provideremote connectivity to one or more systems within the arrangement ofFIG. 2.

The operations and environment analysis module 310 represents acomponent of the remote master control system 300 associated withobtaining and analyzing information to develop instructions/directivesfor components within the arrangement of FIG. 2. The informationanalyzed by the operations and environment analysis module 310 can varywithin examples and may include the information described above withrespect predicting and/or directing the use of BTM power. For instance,the operations and environment analysis module 310 may obtain and accessinformation related to the current power state of computing systemsoperating as part of the flexible datacenters 220 and other datacentersthat the remote master control system 300 has access to. Thisinformation may be used to determine when to adjust power usage or modeof one or more computing systems. In addition, the remote master controlsystem 300 may provide instructions a flexible datacenter 220 to cause asubset of the computing systems to transition into a low power mode toconsume less power while still performing operations at a slower rate.The remote master control system 300 may also use power stateinformation to cause a set of computing systems at a flexible datacenter220 to operate at a higher power consumption mode. In addition, theremote master control system 300 may transition computing systems intosleep states or power on/off based on information analyzed by theoperations and environment analysis module 310.

In some examples, the operations and environment analysis module 310 mayuse location, weather, activity levels at the flexible datacenters orthe generation station, and power cost information to determine controlstrategies for one or more components in the arrangement of FIG. 2. Forinstance, the remote master control system 300 may use locationinformation for one or more datacenters to anticipate potential weatherconditions that could impact access to power. In addition, theoperations and environment analysis module 310 may assist the remotemaster control system 300 determine whether to transfer computationaloperations between datacenters based on various economic and powerfactors.

The queue system 312 represents a queue capable of organizingcomputational operations to be performed by one or more datacenters.Upon receiving a request to perform a computational operation, theremote master control system 300 may assign the computational operationto the queue until one or more computing systems are available tosupport the computational operation. The queue system 312 may be usedfor organizing and transferring computational tasks in real time.

The organizational design of the queue system 312 may vary withinexamples. In some examples, the queue system 312 may organizeindications (e.g., tags, pointers) to sets of computational operationsrequested by various enterprises. The queue system 312 may operate as aFirst-In-First-Out (FIFO) data structure. In a FIFO data structure, thefirst element added to the queue will be the first one to be removed. Assuch, the queue system 312 may include one or more queues that operateusing the FIFO data structure.

In some examples, one or more queues within the queue system 312 may useother designs of queues, including rules to rank or organize queues in aparticular manner that can prioritize some sets of computationaloperations over others. The rules may include one or more of anestimated cost and/or revenue to perform each set of computationaloperations, an importance assigned to each set of computationaloperations, and deadlines for initiating or completing each set ofcomputational operations, among others. Examples using a queue systemare further described below with respect to FIG. 9.

In some examples, the remote master control system 300 may be configuredto monitor one or more auctions to obtain computational operations fordatacenters to support. Particularly, the remote master control system300 may use resource availability and power prices to develop and submitbids to an external or internal auction system for the right to supportparticular computational operations. As a result, the remote mastercontrol system 300 may identify computational operations that could besupported at one or more flexible datacenters 220 at low costs.

FIG. 4 is a block diagram of a generation station 400, according to oneor more example embodiments. Generation station 202 may take the form ofgeneration station 400, or may include less than all components ingeneration station 400, different components than in generation station400, and/or more components than in generation station 400. Thegeneration station 400 includes power generation equipment 401, acommunication interface 408, a behind-the-meter interface 406, a gridinterface 404, a user interface 410, a generation station control system414, and power transformation equipment 402. The power generationequipment 210 may take the form of power generation equipment 401, ormay include less than all components in power generation equipment 401,different components than in power generation equipment 401, and/or morecomponents than in power generation equipment 401. Generation stationcontrol system 216 may take the form of generation station controlsystem 414, or may include less than all components in generationstation control system 414, different components than in generationstation control system 414, and/or more components than in generationstation control system 414. Some or all of the components generationstation 400 may be connected via a communication interface 516. Thesecomponents are illustrated in FIG. 4 to convey an example configurationfor the generation station 400 (corresponding to generation station 202shown in FIG. 2). In other examples, the generation station 400 mayinclude more or fewer components in other arrangements.

The generation station 400 can correspond to any type of grid-connectedutility-scale power producer capable of supplying power to one or moreloads. The size, amount of power generated, and other characteristics ofthe generation station 400 may differ within examples. For instance, thegeneration station 400 may be a power producer that provides powerintermittently. The power generation may depend on monitored powerconditions, such as weather at the location of the generation station400 and other possible conditions. As such, the generation station 400may be a temporary arrangement, or a permanent facility, configured tosupply power. The generation station 400 may supply BTM power to one ormore loads and supply metered power to the electrical grid.Particularly, the generation station 400 may supply power to the grid asshown in the arrangement of FIG. 2.

The power generation equipment 401 represents the component orcomponents configured to generate utility-scale power. As such, thepower generation equipment 401 may depend on the type of facility thatthe generation station 400 corresponds to. For instance, the powergeneration equipment 401 may correspond to electric generators thattransform kinetic energy into electricity. The power generationequipment 401 may use electromagnetic induction to generate power. Inother examples, the power generation equipment 401 may utilizeelectrochemistry to transform chemical energy into power. The powergeneration equipment 401 may use the photovoltaic effect to transformlight into electrical energy. In some examples, the power generationequipment 401 may use turbines to generate power. The turbines may bedriven by, for example, wind, water, steam or burning gas. Otherexamples of power production are possible.

The communication interface 408 can enable the generation station 400 tocommunicate with other components within the arrangement of FIG. 2. Assuch, the communication interface 408 may operate similarly to thecommunication interface 306 of the remote master control system 300 andthe communication interface 503 of the flexible datacenter 500.

The generation station control system 414 may be one or more computingsystems configured to control various aspects of the generation station400.

The BTM interface 406 is a module configured to enable the powergeneration equipment 401 to supply BTM power to one or more loads andmay include multiple components. The arrangement of the BTM interface406 may differ within examples based on various factors, such as thenumber of flexible datacenters 220 (or 500) coupled to the generationstation 400, the proximity of the flexible datacenters 220 (or 500), andthe type of generation station 400, among others. In some examples, theBTM interface 406 may be configured to enable power delivery to one ormore flexible datacenters positioned near the generation station 400.Alternatively, the BTM interface 406 may also be configured to enablepower delivery to one or more flexible datacenters 220 (or 500)positioned remotely from the generation station 400.

The grid interface 404 is a module configured to enable the powergeneration equipment 401 to supply power to the grid and may includemultiple components. As such, the grid interface 404 may couple to oneor more transmission lines (e.g., transmission lines 404 a shown in FIG.2) to enable delivery of power to the grid.

The user interface 410 represents an interface that enablesadministrators and/or other entities to communicate with the generationstation 400. As such, the user interface 410 may have a configurationthat resembles the configuration of the user interface 308 shown in FIG.3. An operator may utilize the user interface 410 to control or monitoroperations at the generation station 400.

The power transformation equipment 402 represents equipment that can beutilized to enable power delivery from the power generation equipment401 to the loads and to transmission lines linked to the grid. Examplepower transformation equipment 402 includes, but is not limited to,transformers, inverters, phase converters, and power conditioners.

FIG. 5 shows a block diagram of a flexible datacenter 500, according toone or more example embodiments. Flexible datacenters 220 may take theform of flexible datacenter 500, or may include less than all componentsin flexible datacenter 500, different components than in flexibledatacenter 500, and/or more components than in flexible datacenter 500.In the example embodiment shown in FIG. 5, the flexible datacenter 500includes a power input system 502, a communication interface 503, adatacenter control system 504, a power distribution system 506, aclimate control system 508, one or more sets of computing systems 512,and a queue system 514. These components are shown connected by acommunication bus 528. In other embodiments, the configuration offlexible datacenter 500 can differ, including more or fewer components.In addition, the components within flexible datacenter 500 may becombined or further divided into additional components within otherembodiments.

The example configuration shown in FIG. 5 represents one possibleconfiguration for a flexible datacenter. As such, each flexibledatacenter may have a different configuration when implemented based ona variety of factors that may influence its design, such as location andtemperature that the location, particular uses for the flexibledatacenter, source of power supplying computing systems within theflexible datacenter, design influence from an entity (or entities) thatimplements the flexible datacenter, and space available for the flexibledatacenter. Thus, the embodiment of flexible datacenter 220 shown inFIG. 2 represents one possible configuration for a flexible datacenterout of many other possible configurations.

The flexible datacenter 500 may include a design that allows fortemporary and/or rapid deployment, setup, and start time for supportingcomputational operations. For instance, the flexible datacenter 500 maybe rapidly deployed at a location near a source of generation stationpower (e.g., near a wind farm or solar farm). Rapid deployment mayinvolve positioning the flexible datacenter 500 at a target location andinstalling and/or configuring one or more racks of computing systemswithin. The racks may include wheels to enable swift movement of thecomputing systems. Although the flexible datacenter 500 couldtheoretically be placed anywhere, transmission losses may be minimizedby locating it proximate to BTM power generation.

The physical construction and layout of the flexible datacenter 500 canvary. In some instances, the flexible datacenter 500 may utilize a metalcontainer (e.g., a metal container 602 shown in FIG. 6A). In general,the flexible datacenter 500 may utilize some form of secure weatherproofhousing designed to protect interior components from wind, weather, andintrusion. The physical construction and layout of example flexibledatacenters are further described with respect to FIGS. 6A-6B.

Within the flexible datacenter 500, various internal components enablethe flexible datacenter 500 to utilize power to perform some form ofoperations. The power input system 502 is a module of the flexibledatacenter 500 configured to receive external power and input the powerto the different components via assistance from the power distributionsystem 506. As discussed with respect to FIG. 2, the sources of externalpower feeding a flexible datacenter can vary in both quantity and type(e.g., the generation stations 202, 400, grid-power, energy storagesystems). Power input system 502 includes a BTM power input sub-system522, and may additionally include other power input sub-systems (e.g., agrid-power input sub-system 524 and/or an energy storage inputsub-system 526). In some instances, the quantity of power inputsub-systems may depend on the size of the flexible datacenter and thenumber and/or type of computing systems being powered. In an exampleembodiment, the flexible datacenter may use grid power as the primarypower supply.

In some embodiments, the power input system 502 may include some or allof flexible datacenter Power Equipment 220B. The power input system 502may be designed to obtain power in different forms (e.g., single phaseor three-phase behind-the-meter alternating current (“AC”) voltage,and/or direct current (“DC”) voltage). As shown, the power input system502 includes a BTM power input sub-system 522, a grid power inputsub-system 524, and an energy input sub-system 526. These sub-systemsare included to illustrate example power input sub-systems that theflexible datacenter 500 may utilize, but other examples are possible. Inaddition, in some instances, these sub-systems may be usedsimultaneously to supply power to components of the flexible datacenter500. The sub-systems may also be used based on available power sources.

In some implementations, the BTM power input sub-system 522 may includeone or more AC-to-AC step-down transformers used to step down suppliedmedium-voltage AC to low voltage AC (e.g., 120V to 600V nominal) used topower computing systems 512 and/or other components of flexibledatacenter 500. The power input system 502 may also directly receivesingle-phase low voltage AC from a generation station as BTM power, fromgrid power, or from a stored energy system such as energy storage system218. In some implementations, the power input system 502 may providesingle-phase AC voltage to the datacenter control system 504 (and/orother components of flexible datacenter 500) independent of powersupplied to computing systems 512 to enable the datacenter controlsystem 504 to perform management operations for the flexible datacenter500. For instance, the grid power input sub-system 524 may use gridpower to supply power to the datacenter control system 504 to ensurethat the datacenter control system 504 can perform control operationsand communicate with the remote master control system 300 (or 262)during situations when BTM power is not available. As such, thedatacenter control system 504 may utilize power received from the powerinput system 502 to remain powered to control the operation of flexibledatacenter 500, even if the computational operations performed by thecomputing system 512 are powered intermittently. In some instances, thedatacenter control system 504 may switch into a lower power mode toutilize less power while still maintaining the ability to perform somefunctions.

The power distribution system 506 may distribute incoming power to thevarious components of the flexible datacenter 500. For instance, thepower distribution system 506 may direct power (e.g., single-phase orthree-phase AC) to one or more components within flexible datacenter500. In some embodiments, the power distribution system 506 may includesome or all of flexible datacenter Power Equipment 220B.

In some examples, the power input system 502 may provide three phases ofthree-phase AC voltage to the power distribution system 506. The powerdistribution system 506 may controllably provide a single phase of ACvoltage to each computing system or groups of computing systems 512disposed within the flexible datacenter 500. The datacenter controlsystem 504 may controllably select which phase of three-phase nominal ACvoltage that power distribution system 506 provides to each computingsystem 512 or groups of computing systems 512. This is one examplemanner in which the datacenter control system 504 may modulate powerdelivery (and load at the flexible datacenter 500) by ramping-upflexible datacenter 500 to fully operational status, ramping-downflexible datacenter 500 to offline status (where only datacenter controlsystem 504 remains powered), reducing load by withdrawing power deliveryfrom, or reducing power to, one or more of the computing systems 512 orgroups of the computing systems 512, or modulating power factorcorrection for the generation station 300 (or 202) by controllablyadjusting which phases of three-phase nominal AC voltage are used by oneor more of the computing systems 512 or groups of the computing systems512. The datacenter control system 504 may direct power to certain setsof computing systems based on computational operations waiting forcomputational resources within the queue system 514. In someembodiments, the flexible datacenter 500 may receive BTM DC power topower the computing systems 512.

One of ordinary skill in the art will recognize that a voltage level ofthree-phase AC voltage may vary based on an application or design andthe type or kind of local power generation. As such, a type, kind, orconfiguration of the operational AC-to-AC step down transformer (notshown) may vary based on the application or design. In addition, thefrequency and voltage level of three-phase AC voltage, single-phase ACvoltage, and DC voltage may vary based on the application or design inaccordance with one or more embodiments.

As discussed above, the datacenter control system 504 may performoperations described herein, such as dynamically modulating powerdelivery to one or more of the computing systems 512 disposed withinflexible datacenter 500. For instance, the datacenter control system 504may modulate power delivery to one or more of the computing systems 512based on various factors, such as BTM power availability or anoperational directive from a generation station 262 or 300 controlsystem, a remote master control system 262 or 300, or a grid operator.In some examples, the datacenter control system 504 may providecomputational operations to sets of computing systems 512 and modulatepower delivery based on priorities assigned to the computationaloperations. For instance, an important computational operation (e.g.,based on a deadline for execution and/or price paid by an entity) may beassigned to a particular computing system or set of computing systems512 that has the capacity, computational abilities to support thecomputational operation. In addition, the datacenter control system 504may also prioritize power delivery to the computing system or set ofcomputing systems 512.

In some example, the datacenter control system 504 may further providedirectives to one or more computing systems to change operations in somemanner. For instance, the datacenter control system 504 may cause one ormore computing systems 512 to operate at a lower or higher frequency,change clock cycles, or operate in a different power consumption mode(e.g., a low power mode). These abilities may vary depending on types ofcomputing systems 512 available at the flexible datacenter 500. As aresult, the datacenter control system 504 may be configured to analyzethe computing systems 512 available either on a periodic basis (e.g.,during initial set up of the flexible datacenter 500) or in anothermanner (e.g., when a new computational operation is assigned to theflexible datacenter 500).

The datacenter control system 504 may also implement directives receivedfrom the remote master control system 262 or 300. For instance, theremote master control system 262 or 300 may direct the flexibledatacenter 500 to switch into a low power mode. As a result, one or moreof the computing systems 512 and other components may switch to the lowpower mode in response.

The datacenter control system 504 may utilize the communicationinterface 503 to communicate with the remote master control system 262or 300, other datacenter control systems of other datacenters, and otherentities. As such, the communication interface 503 may includecomponents and operate similar to the communication interface 306 of theremote master control system 300 described with respect to FIG. 4.

The flexible datacenter 500 may also include a climate control system508 to maintain computing systems 512 within a desired operationaltemperature range. The climate control system 508 may include variouscomponents, such as one or more air intake components, an evaporativecooling system, one or more fans, an immersive cooling system, an airconditioning or refrigerant cooling system, and one or more air outtakecomponents. One of ordinary skill in the art will recognize that anysuitable heat extraction system configured to maintain the operation ofcomputing systems 512 within the desired operational temperature rangemay be used.

The flexible datacenter 500 may further include an energy storage system510. The energy storage system 510 may store energy for subsequent useby computing systems 512 and other components of flexible datacenter500. For instance, the energy storage system 510 may include a batterysystem. The battery system may be configured to convert AC voltage to DCvoltage and store power in one or more storage cells. In some instances,the battery system may include a DC-to-AC inverter configured to convertDC voltage to AC voltage, and may further include an AC phase-converter,to provide AC voltage for use by flexible datacenter 500.

The energy storage system 510 may be configured to serve as a backupsource of power for the flexible datacenter 500. For instance, theenergy storage system 510 may receive and retain power from a BTM powersource at a low cost (or no cost at all). This low-cost power can thenbe used by the flexible datacenter 500 at a subsequent point, such aswhen BTM power costs more. Similarly, the energy storage system 510 mayalso store energy from other sources (e.g., grid power). As such, theenergy storage system 510 may be configured to use one or more of thesub-systems of the power input system 502.

In some examples, the energy storage system 510 may be external to theflexible datacenter 500. For instance, the energy storage system 510 maybe an external source that multiple flexible datacenters utilize forback-up power.

The computing systems 512 represent various types of computing systemsconfigured to perform computational operations. Performance ofcomputational operations include a variety of tasks that one or morecomputing systems may perform, such as data storage, calculations,application processing, parallel processing, data manipulation,cryptocurrency mining, and maintenance of a distributed ledger, amongothers. As shown in FIG. 5, the computing systems 512 may include one ormore CPUs 516, one or more GPUs 518, and/or one or moreApplication-Specific Integrated Circuits (ASIC's) 520. Each type ofcomputing system 512 may be configured to perform particular operationsor types of operations.

Due to different performance features and abilities associated with thedifferent types of computing systems, the datacenter control system 504may determine, maintain, and/or relay this information about the typesand/or abilities of the computing systems, quantity of each type, andavailability to the remote master control system 262 or 300 on a routinebasis (e.g., periodically or on-demand). This way, the remote mastercontrol system 262 or 300 may have current information about theabilities of the computing systems 512 when distributing computationaloperations for performance at one or more flexible datacenters.Particularly, the remote master control system 262 or 300 may assigncomputational operations based on various factors, such as the types ofcomputing systems available and the type of computing systems requiredby each computing operation, the availability of the computing systems,whether computing systems can operate in a low power mode, and/or powerconsumption and/or costs associated with operating the computingsystems, among others.

The quantity and arrangement of these computing systems 512 may varywithin examples. In some examples, the configuration and quantity ofcomputing systems 512 may depend on various factors, such as thecomputational tasks that are performed by the flexible datacenter 500.In other examples, the computing systems 512 may include other types ofcomputing systems as well, such as DSPs, SIMDs, neural processors,and/or quantum processors.

As indicated above, the computing systems 512 can perform variouscomputational operations, including in different configurations. Forinstance, each computing system may perform a particular computationaloperation unrelated to the operations performed at other computingsystems. Groups of the computing systems 512 may also be used to worktogether to perform computational operations.

In some examples, multiple computing systems may perform the samecomputational operation in a redundant configuration. This redundantconfiguration creates a back-up that prevents losing progress on thecomputational operation in situations of a computing failure orintermittent operation of one or more computing systems. In addition,the computing systems 512 may also perform computational operationsusing a check point system. The check point system may enable a firstcomputing system to perform operations up to a certain point (e.g., acheckpoint) and switch to a second computing system to continueperforming the operations from that certain point. The check pointsystem may also enable the datacenter control system 504 to communicatestatuses of computational operations to the remote master control system262 or 300. This can further enable the remote master control system 262300 to transfer computational operations between different flexibledatacenters allowing computing systems at the different flexibledatacenters to resume support of computational operations based on thecheck points.

The queue system 514 may operate similar to the queue system 312 of theremote master control system 300 shown in FIG. 3. Particularly, thequeue system 514 may help store and organize computational tasksassigned for performance at the flexible datacenter 500. In someexamples, the queue system 514 may be part of a distributed queue systemsuch that each flexible datacenter in a fleet of flexible datacenterincludes a queue, and each queue system 514 may be able to communicatewith other queue systems. In addition, the remote master control system262 or 300 may be configured to assign computational tasks to the queueslocated at each flexible datacenter (e.g., the queue system 514 of theflexible datacenter 500). As such, communication between the remotemaster control system 262 or 300 and the datacenter control system 504and/or the queue system 514 may allow organization of computationaloperations for the flexible datacenter 500 to support.

FIG. 6A shows another structural arrangement for a flexible datacenter,according to one or more example embodiments. The particular structuralarrangement shown in FIG. 6A may be implemented at flexible datacenter500. The illustration depicts the flexible datacenter 500 as a mobilecontainer 702 equipped with the power input system 502, the powerdistribution system 506, the climate control system 508, the datacentercontrol system 504, and the computing systems 512 arranged on one ormore racks 604. These components of flexible datacenter 500 may bearranged and organized according to an example structural regionarrangement. As such, the example illustration represents one possibleconfiguration for the flexible datacenter 500, but others are possiblewithin examples.

As discussed above, the structural arrangement of the flexibledatacenter 500 may depend on various factors, such as the ability tomaintain temperature within the mobile container 602 within a desiredtemperature range. The desired temperature range may depend on thegeographical location of the mobile container 602 and the type andquantity of the computing systems 512 operating within the flexibledatacenter 500 as well as other possible factors. As such, the differentdesign elements of the mobile container 602 including the inner contentsand positioning of components may depend on factors that aim to maximizethe use of space within mobile container 602, lower the amount of powerrequired to cool the computing systems 512, and make setup of theflexible datacenter 500 efficient. For instance, a first flexibledatacenter positioned in a cooler geographic region may include lesscooling equipment than a second flexible datacenter positioned in awarmer geographic region.

As shown in FIG. 6A, the mobile container 602 may be a storage trailerdisposed on permanent or removable wheels and configured for rapiddeployment. In other embodiments, the mobile container 602 may be astorage container (not shown) configured for placement on the ground andpotentially stacked in a vertical or horizontal manner (not shown). Instill other embodiments, the mobile container 602 may be an inflatablecontainer, a floating container, or any other type or kind of containersuitable for housing a mobile flexible datacenter. As such, the flexibledatacenter 500 may be rapidly deployed on site near a source ofunutilized behind-the-meter power generation. And in still otherembodiments, the flexible datacenter 500 might not include a mobilecontainer. For example, the flexible datacenter 500 may be situatedwithin a building or another type of stationary environment.

FIG. 6B shows the computing systems 512 in a straight-line configurationfor installation within the flexible datacenter 500, according to one ormore example embodiments. As indicated above, the flexible datacenter500 may include a plurality of racks 604, each of which may include oneor more computing systems 512 disposed therein. As discussed above, thepower input system 502 may provide three phases of AC voltage to thepower distribution system 506. In some examples, the power distributionsystem 506 may controllably provide a single phase of AC voltage to eachcomputing system 512 or group of computing systems 512 disposed withinthe flexible datacenter 500. As shown in FIG. 6B, for purposes ofillustration only, eighteen total racks 604 are divided into a firstgroup of six racks 606, a second group of six racks 608, and a thirdgroup of six racks 610, where each rack contains eighteen computingsystems 512. The power distribution system (506 of FIG. 5) may, forexample, provide a first phase of three-phase AC voltage to the firstgroup of six racks 606, a second phase of three-phase AC voltage to thesecond group of six racks 608, and a third phase of three-phase ACvoltage to the third group of six racks 610. In other embodiments, thequantity of racks and computing systems can vary.

FIG. 7 shows a control distribution system 700 of the flexibledatacenter 500 according to one or more example embodiments. The system700 includes a grid operator 702, a generation station control system216, a remote master control system 300, and a flexible datacenter 500.As such, the system 700 represents one example configuration forcontrolling operations of the flexible datacenter 500, but otherconfigurations may include more or fewer components in otherarrangements.

The datacenter control system 504 may independently or cooperativelywith one or more of the generation station control system 414, theremote master control system 300, and/or the grid operator 702 modulatepower at the flexible datacenter 500. During operations, the powerdelivery to the flexible datacenter 500 may be dynamically adjustedbased on conditions or operational directives. The conditions maycorrespond to economic conditions (e.g., cost for power, aspects ofcomputational operations to be performed), power-related conditions(e.g., availability of the power, the sources offering power), demandresponse, and/or weather-related conditions, among others.

The generation station control system 414 may be one or more computingsystems configured to control various aspects of a generation station(not independently illustrated, e.g., 216 or 400). As such, thegeneration station control system 414 may communicate with the remotemaster control system 300 over a networked connection 706 and with thedatacenter control system 704 over a networked or other data connection708.

As discussed with respect to FIGS. 2 and 3, the remote master controlsystem 300 can be one or more computing systems located offsite, butconnected via a network connection 710 to the datacenter control system504. The remote master control system 300 may provide supervisorycontrols or override control of the flexible datacenter 500 or a fleetof flexible datacenters (not shown).

The grid operator 702 may be one or more computing systems that areconfigured to control various aspects of the power grid (notindependently illustrated) that receives power from the generationstation. The grid operator 702 may communicate with the generationstation control system 300 over a networked or other data connection712.

The datacenter control system 504 may monitor BTM power conditions atthe generation station and determine when a datacenter ramp-up conditionis met. The BTM power availability may include one or more of excesslocal power generation, excess local power generation that the gridcannot accept, local power generation that is subject to economiccurtailment, local power generation that is subject to reliabilitycurtailment, local power generation that is subject to power factorcorrection, conditions where the cost for power is economically viable(e.g., low cost to obtain power), low priced power, situations wherelocal power generation is prohibitively low, start up situations,transient situations, or testing situations where there is an economicadvantage to using locally generated behind-the-meter power generation,specifically power available at little to no cost and with no associatedtransmission or distribution losses or costs. For example, a datacentercontrol system may analyze future workload and near term weatherconditions at the flexible datacenter.

In some instances, the datacenter ramp-up condition may be met if thereis sufficient behind-the-meter power availability and there is nooperational directive from the generation station control system 414,the remote master control system 300, or the grid operator 702 to gooffline or reduce power. As such, the datacenter control system 504 mayenable 714 the power input system 502 to provide power to the powerdistribution system 506 to power the computing systems 512 or a subsetthereof.

The datacenter control system 504 may optionally direct one or morecomputing systems 512 to perform predetermined computational operations(e.g., distributed computing processes). For example, if the one or morecomputing systems 512 are configured to perform blockchain hashingoperations, the datacenter control system 504 may direct them to performblockchain hashing operations for a specific blockchain application,such as, for example, Bitcoin, Litecoin, or Ethereum. Alternatively, oneor more computing systems 512 may be configured to performhigh-throughput computing operations and/or high performance computingoperations.

The remote master control system 300 may specify to the datacentercontrol system 504 what sufficient behind-the-meter power availabilityconstitutes, or the datacenter control system 504 may be programmed witha predetermined preference or criteria on which to make thedetermination independently. For example, in certain circumstances,sufficient behind-the-meter power availability may be less than thatrequired to fully power the entire flexible datacenter 500. In suchcircumstances, the datacenter control system 504 may provide power toonly a subset of computing systems, or operate the plurality ofcomputing systems in a lower power mode, that is within the sufficient,but less than full, range of power that is available. In addition, thecomputing systems 512 may adjust operational frequency, such asperforming more or less processes during a given duration. The computingsystems 512 may also adjust internal clocks via over-clocking orunder-clocking when performing operations.

While the flexible datacenter 500 is online and operational, adatacenter ramp-down condition may be met when there is insufficient oranticipated to be insufficient, behind-the-meter power availability orthere is an operational directive from the generation station controlsystem 414, the remote master control system 300, or the grid operator702. The datacenter control system 504 may monitor and determine whenthere is insufficient, or anticipated to be insufficient,behind-the-meter power availability. As noted above, sufficiency may bespecified by the remote master control system 300 or the datacentercontrol system 504 may be programmed with a predetermined preference orcriteria on which to make the determination independently.

An operational directive may be based on current dispatch-ability,forward looking forecasts for when behind-the-meter power is, or isexpected to be, available, economic considerations, reliabilityconsiderations, operational considerations, or the discretion of thegeneration station control system 414, the remote master control system300, or the grid operator 702. For example, the generation stationcontrol system 414, the remote master control system 300, or the gridoperator 702 may issue an operational directive to flexible datacenter500 to go offline and power down. When the datacenter ramp-downcondition is met, the datacenter control system 504 may disable powerdelivery to the plurality of computing systems (e.g., 512). Thedatacenter control system 504 may disable 714 the power input system 502from providing power (e.g., three-phase nominal AC voltage) to the powerdistribution system 506 to power down the computing systems 512 whilethe datacenter control system 504 remains powered and is capable ofreturning service to operating mode at the flexible datacenter 500 whenbehind-the-meter power becomes available again.

While the flexible datacenter 500 is online and operational, changedconditions or an operational directive may cause the datacenter controlsystem 504 to modulate power consumption by the flexible datacenter 500.The datacenter control system 504 may determine, or the generationstation control system 414, the remote master control system 300, or thegrid operator 702 may communicate, that a change in local conditions mayresult in less power generation, availability, or economic feasibility,than would be necessary to fully power the flexible datacenter 500. Insuch situations, the datacenter control system 504 may take steps toreduce or stop power consumption by the flexible datacenter 500 (otherthan that required to maintain operation of datacenter control system504).

Alternatively, the generation station control system 414, the remotemaster control system 300, or the grid operator 702, may issue anoperational directive to reduce power consumption for any reason, thecause of which may be unknown. In response, the datacenter controlsystem 504 may dynamically reduce or withdraw power delivery to one ormore computing systems 512 to meet the dictate. The datacenter controlsystem 504 may controllably provide three-phase nominal AC voltage to asmaller subset of computing systems (e.g., 512) to reduce powerconsumption. The datacenter control system 504 may dynamically reducethe power consumption of one or more computing systems by reducing theiroperating frequency or forcing them into a lower power mode through anetwork directive.

Similarly, the flexible datacenter 500 may ramp up power consumptionbased on various conditions. For instance, the datacenter control system504 may determine, or the generation control system 414, the remotemaster control system 300, or the grid operator 702 may communicate,that a change in local conditions may result in greater powergeneration, availability, or economic feasibility. In such situations,the datacenter control system 504 may take steps to increase powerconsumption by the flexible datacenter 500.

Alternatively, the generation station control system 414, the remotemaster control system 300, or the grid operator 702, may issue anoperational directive to increase power consumption for any reason, thecause of which may be unknown. In response, the datacenter controlsystem 504 may dynamically increase power delivery to one or morecomputing systems 512 (or operations at the computing systems 512) tomeet the dictate. For instance, one or more computing systems 512 maytransition into a higher power mode, which may involve increasing powerconsumption and/or operation frequency.

One of ordinary skill in the art will recognize that datacenter controlsystem 504 may be configured to have a number of differentconfigurations, such as a number or type or kind of the computingsystems 512 that may be powered, and in what operating mode, thatcorrespond to a number of different ranges of sufficient and availablebehind-the-meter power. As such, the datacenter control system 504 maymodulate power delivery over a variety of ranges of sufficient andavailable unutilized behind-the-meter power availability.

FIG. 8 shows a control distribution system 800 of a fleet of flexibledatacenters according to one or more example embodiments. The controldistribution system 800 of the flexible datacenter 500 shown anddescribed with respect to FIG. 7 may be extended to a fleet of flexibledatacenters as illustrated in FIG. 8. For example, a first generationstation (not independently illustrated), such as a wind farm, mayinclude a first plurality of flexible datacenters 802, which may becollocated or distributed across the generation station. A secondgeneration station (not independently illustrated), such as another windfarm or a solar farm, may include a second plurality of flexibledatacenters 804, which may be collocated or distributed across thegeneration station. One of ordinary skill in the art will recognize thatthe number of flexible datacenters deployed at a given station and thenumber of stations within the fleet may vary based on an application ordesign in accordance with one or more example embodiments.

The remote master control system 300 may provide directive to datacentercontrol systems of the fleet of flexible datacenters in a similar mannerto that shown and described with respect to FIG. 7, with the addedflexibility to make high level decisions with respect to fleet that maybe counterintuitive to a given station. The remote master control system300 may make decisions regarding the issuance of operational directivesto a given generation station based on, for example, the status of eachgeneration station where flexible datacenters are deployed, the workloaddistributed across fleet, and the expected computational demand requiredfor one or both of the expected workload and predicted poweravailability. In addition, the remote master control system 300 mayshift workloads from the first plurality of flexible datacenters 802 tothe second plurality of flexible datacenters 804 for any reason,including, for example, a loss of BTM power availability at onegeneration station and the availability of BTM power at anothergeneration station. As such, the remote master control system 300 maycommunicate with the generation station control systems 806A, 806B toobtain information that can be used to organize and distributecomputational operations to the fleets of flexible datacenters 802, 804.

FIG. 9 shows a queue distribution arrangement for a traditionaldatacenter 902 and a flexible datacenter 500, according to one or moreexample embodiments. The arrangement of FIG. 9 includes a flexibledatacenter 500, a traditional datacenter 902, a queue system 312, a setof communication links 916, 918, 920A, 920B, and the remote mastercontrol system 300. The arrangement of FIG. 9 represents an exampleconfiguration scheme that can be used to distribute computing operationsusing a queue system 312 between the traditional datacenter 902 and oneor more flexible datacenters. In other examples, the arrangement of FIG.9 may include more or fewer components in other potentialconfigurations. For instance, the arrangement of FIG. 9 may not includethe queue system 312 or may include routes that bypass the queue system312.

The arrangement of FIG. 9 may enable computational operations requestedto be performed by entities (e.g., companies). As such, the arrangementof FIG. 9 may use the queue system 312 to organize incomingcomputational operations requests to enable efficient distribution tothe flexible datacenter 500 and the critical traditional datacenter 902.Particularly, the arrangement of FIG. 9 may use the queue system 312 toorganize sets of computational operations thereby increasing the speedof distribution and performance of the different computationaloperations among datacenters. As a result, the use of the queue system312 may reduce time to complete operations and reduce costs.

In some examples, one or more components, such as the datacenter controlsystem 504, the remote master control system 300, the queue system 312,or the control system 936, may be configured to identify situations thatmay arise where using the flexible datacenter 500 can reduce costs orincrease productivity of the system, as compared to using thetraditional datacenter 902 for computational operations. For example, acomponent within the arrangement of FIG. 9 may identify when usingbehind-the-meter power to power the computing systems 512 within theflexible datacenter 500 is at a lower cost compared to using thecomputing systems 934 within the traditional datacenter 902 that arepowered by grid power. Additionally, a component in the arrangement ofFIG. 9 may be configured to determine situations when offloadingcomputational operations from the traditional datacenter 902 indirectly(i.e., via the queue system 312) or directly (i.e., bypassing the queuesystem 312) to the flexible datacenter 500 can increase the performanceallotted to the computational operations requested by an entity (e.g.,reduce the time required to complete time-sensitive computationaloperations).

In some examples, the datacenter control system 504 may monitor activityof the computing systems 512 within the flexible datacenter 500 and usethe respective activity levels to determine when to obtain computationaloperations from the queue system 312. For instance, the datacentercontrol system 504 may analyze various factors prior to requesting oraccessing a set of computational operations or an indication of thecomputational operations for the computing systems 512 to perform. Thevarious factors may include power availability at the flexibledatacenter 500 (e.g., either stored or from a BTM source), availabilityof the computing systems 512 (e.g., percentage of computing systemsavailable), type of computational operations available, estimated costto perform the computational operations at the flexible datacenter 500,cost for power, cost for power relative to cost for grid power, andinstructions from other components within the system, among others. Thedatacenter control system 504 may analyze one or more of the factorswhen determining whether to obtain a new set of computational operationsfor the computing systems 512 to perform. In such a configuration, thedatacenter control system 504 manages the activity of the flexibledatacenter 500, including determining when to acquire new sets ofcomputational operations when capacity among the computing systems 512permit.

In other examples, a component (e.g., the remote master control system300) within the system may assign or distribute one or more sets ofcomputational operations organized by the queue system 312 to theflexible datacenter 500. For example, the remote master control system300 may manage the queue system 312, including the distribution ofcomputational operations organized by the queue system 312 to theflexible datacenter 500 and the traditional datacenter 902. The remotemaster control system 300 may utilize to information described withrespect to the Figures above to determine when to assign computationaloperations to the flexible datacenter 500.

The traditional datacenter 902 may include a power input system 930, apower distribution system 932, a datacenter control system 936, and aset of computing systems 934. The power input system 930 may beconfigured to receive power from a power grid and distribute the powerto the computing systems 934 via the power distribution system 932. Thedatacenter control system 936 may monitor activity of the computingsystems 934 and obtain computational operations to perform from thequeue system 312. The datacenter control system 936 may analyze variousfactors prior to requesting or accessing a set of computationaloperations or an indication of the computational operations for thecomputing systems 934 to perform. A component (e.g., the remote mastercontrol system 300) within the arrangement of FIG. 9 may assign ordistribute one or more sets of computational operations organized by thequeue system 312 to the traditional datacenter 902.

The communication link 916 represents one or more links that may serveto connect the flexible datacenter 500, the traditional datacenter 902,and other components within the system (e.g., the remote master controlsystem 300, the queue system 312—connections not shown). In particular,the communication link 916 may enable direct or indirect communicationbetween the flexible datacenter 500 and the traditional datacenter 902.The type of communication link 916 may depend on the locations of theflexible datacenter 500 and the traditional datacenter 902. Withinembodiments, different types of communication links can be used,including but not limited to WAN connectivity, cloud-based connectivity,and wired and wireless communication links.

The queue system 312 represents an abstract data type capable oforganizing computational operation requests received from entities. Aseach request for computational operations are received, the queue system312 may organize the request in some manner for subsequent distributionto a datacenter. Different types of queues can make up the queue system312 within embodiments. The queue system 312 may be a centralized queuethat organizes all requests for computational operations. As acentralized queue, all incoming requests for computational operationsmay be organized by the centralized queue.

In other examples, the queue system 312 may be distributed consisting ofmultiple queue sub-systems. In the distributed configuration, the queuesystem 312 may use multiple queue sub-systems to organize different setsof computational operations. Each queue sub-system may be used toorganize computational operations based on various factors, such asaccording to deadlines for completing each set of computationaloperations, locations of enterprises submitting the computationaloperations, economic value associated with the completion ofcomputational operations, and quantity of computing resources requiredfor performing each set of computational operations. For instance, afirst queue sub-system may organize sets of non-intensive computationaloperations and a second queue sub-system may organize sets of intensivecomputational operations. In some examples, the queue system 312 mayinclude queue sub-systems located at each datacenter. This way, eachdatacenter (e.g., via a datacenter control system) may organizecomputational operations obtained at the datacenter until computingsystems are able to start executing the computational operations. Insome examples, the queue system 312 may move computational operationsbetween different computing systems or different datacenters inreal-time.

Within the arrangement of FIG. 9, the queue system 312 is shownconnected to the remote master control system 300 via the communicationlink 918. In addition, the queue system 312 is also shown connected tothe flexible datacenter via the communication 920A and to thetraditional datacenter 902 via the communication link 920B. Thecommunication links 918, 920A, 920B may be similar to the communicationlink 916 and can be various types of communication links withinexamples.

The queue system 312 may include a computing system configured toorganize and maintain queues within the queue system 312. In anotherexample, one or more other components of the system may maintain andsupport queues within the queue system 312. For instance, the remotemaster control system 300 may maintain and support the queue system 312.In other examples, multiple components may maintain and support thequeue system 312 in a distributed manner, such as a blockchainconfiguration.

In some embodiments, the remote master control system 300 may serve asan intermediary that facilitates all communication between flexibledatacenter 500 and the traditional datacenter 902. Particularly, thetraditional datacenter 902 or the flexible datacenter 500 might need totransmit communications to the remote master control system 300 in orderto communicate with the other datacenter. As also shown, the remotemaster control system 300 may connect to the queue system 312 via thecommunication link 918. Computational operations may be distributedbetween the queue system 312 and the remote master control system 300via the communication link 918. The computational operations may betransferred in real-time and mid-performance from one datacenter toanother (e.g., from the traditional datacenter 902 to the flexibledatacenter 500). In addition, the remote master control system 300 maymanage the queue system 312, including providing resources to supportqueues within the queue system 312.

As a result, the remote master control system 300 may offload some orall of the computational operations assigned to the traditionaldatacenter 902 to the flexible datacenter 500. This way, the flexibledatacenter 500 can reduce overall computational costs by using thebehind-the-meter power to provide computational resources to assisttraditional datacenter 902. The remote master control system 300 may usethe queue system 312 to temporarily store and organize the offloadedcomputational operations until a flexible datacenter (e.g., the flexibledatacenter 500) is available to perform them. The flexible datacenter500 consumes behind-the-meter power without transmission or distributioncosts, which lowers the costs associated with performing computationaloperations originally assigned to the traditional datacenter 902. Theremote master control system 300 may further communicate with theflexible datacenter 500 via communication link 922 and the traditionaldatacenter 902 via the communication link 924.

FIG. 10A shows method 1000 of dynamic power consumption at a flexibledatacenter using behind-the-meter power according to one or more exampleembodiments. Other example methods may be used to manipulate the powerdelivery to one or more flexible datacenters.

In step 1010, the datacenter control system, the remote master controlsystem, or another computing system may monitor behind-the-meter poweravailability. In some embodiments, monitoring may include receivinginformation or an operational directive from the generation stationcontrol system or the grid operator corresponding to behind-the-meterpower availability.

In step 1020, the datacenter control system or the remote master controlsystem 300 may determine when a datacenter ramp-up condition is met. Insome embodiments, the datacenter ramp-up condition may be met when thereis sufficient behind-the-meter power availability and there is nooperational directive from the generation station to go offline orreduce power.

In step 1030, the datacenter control system may enable behind-the-meterpower delivery to one or more computing systems. In some instances, theremote mater control system may directly enable BTM power delivery tocomputing systems within the flexible system without instructing thedatacenter control system.

In step 1040, once ramped-up, the datacenter control system or theremote master control system may direct one or more computing systems toperform predetermined computational operations. In some embodiments, thepredetermined computational operations may include the execution of oneor more distributed computing processes, parallel processes, and/orhashing functions, among other types of processes.

While operational, the datacenter control system, the remote mastercontrol system, or another computing system may receive an operationaldirective to modulate power consumption. In some embodiments, theoperational directive may be a directive to reduce power consumption. Insuch embodiments, the datacenter control system or the remote mastercontrol system may dynamically reduce power delivery to one or morecomputing systems or dynamically reduce power consumption of one or morecomputing systems. In other embodiments, the operational directive maybe a directive to provide a power factor correction factor. In suchembodiments, the datacenter control system or the remote master controlsystem may dynamically adjust power delivery to one or more computingsystems to achieve a desired power factor correction factor. In stillother embodiments, the operational directive may be a directive to gooffline or power down. In such embodiments, the datacenter controlsystem may disable power delivery to one or more computing systems.

FIG. 10B shows method 1050 of dynamic power delivery to a flexibledatacenter using behind-the-meter power according to one or moreembodiments. In step 1060, the datacenter control system or the remotemaster control system may monitor behind-the-meter power availability.In certain embodiments, monitoring may include receiving information oran operational directive from the generation station control system orthe grid operator corresponding to behind-the-meter power availability.

In step 1070, the datacenter control system or the remote master controlsystem may determine when a datacenter ramp-down condition is met. Incertain embodiments, the datacenter ramp-down condition may be met whenthere is insufficient behind-the-meter power availability or anticipatedto be insufficient behind-the-meter power availability or there is anoperational directive from the generation station to go offline orreduce power.

In step 1080, the datacenter control system may disable behind-the-meterpower delivery to one or more computing systems. In step 1090, onceramped-down, the datacenter control system remains powered and incommunication with the remote master control system so that it maydynamically power the flexible datacenter when conditions change.

One of ordinary skill in the art will recognize that a datacentercontrol system may dynamically modulate power delivery to one or morecomputing systems of a flexible datacenter based on behind-the-meterpower availability or an operational directive. The flexible datacentermay transition between a fully powered down state (while the datacentercontrol system remains powered), a fully powered up state, and variousintermediate states in between. In addition, flexible datacenter mayhave a blackout state, where all power consumption, including that ofthe datacenter control system is halted. However, once the flexibledatacenter enters the blackout state, it will have to be manuallyrebooted to restore power to datacenter control system. Generationstation conditions or operational directives may cause flexibledatacenter to ramp-up, reduce power consumption, change power factor, orramp-down.

FIG. 11 illustrates a block diagram of a system for implementing controlstrategies based on a power option agreement, according to one or moreembodiments. The system 1100 represents an example arrangement thatincludes a control system (e.g., the remote master control system 262),a load (e.g., one or more of the datacenters 1102, 1104, and 1106), anda power entity 1140, which may establish and operate in accordance witha power option agreement. Additional arrangements are possible withinexamples.

In general, a power option agreement is an agreement between a powerentity 1140 associated with the delivery of power to a load (e.g., agrid operator, power generation station, or local control station) andthe load (e.g., the datacenters 1102-1106). As part of the power optionagreement, the load (e.g., load operator, contracting agent for theload, semi-automated control system associated with the load, and/orautomated control system associated with the load) provides the powerentity 1140 with the right, but not obligation, to reduce the amount ofpower delivered (e.g., grid power) to the load up to an agreed amount ofpower during an agreed upon time interval. In order to provide the powerentity 1140 with this option, the load needs to be using at least theamount of power subject to the option (e.g., a minimum power threshold).For instance, the load may agree to use at least 1 MW of grid power atall times during a specified 24-hour time interval to provide the powerentity 1140 with the option of being able to reduce the amount of powerdelivered to the load by any amount up to 1 MW at any point during thespecified 24-hour time interval. The load may grant the power entity1140 with this option in exchange for a monetary consideration (e.g.,receive power at a reduced price and/or monetary payment if the optionis exercised by the power entity).

The power option agreement may be used by the power entity 1140 toreserve the right to reduce the amount of grid power delivered to theload during a set time frame (e.g., the next 24 hours). For instance,the power entity 1140 may exercise a predefined power option to reducethe amount of grid power delivered to the load during a time when thegrid power may be better redirected to other loads coupled to the powergrid. As such, the power entity 1140 may exercise power optionagreements to balance loads coupled to the power grid. In someembodiments, a power option agreement may also specify other parameters,such as costs associated with different levels of power consumptionand/or maximum power thresholds for the load to operate according to.

To illustrate an example, a power option agreement may specify that aload (e.g., the datacenters 1102-1106) is required to use at least 10 MWor more at all times during the next 12 hours. Thus, the minimum powerthreshold according to the power option agreement is 10 MW and thisminimum power threshold extends across the time interval of the next 12hours. In order to comply with the agreement, the load must subsequentlyoperate using 10 MW or more power at all times during the next 12 hours.This way, the load can accommodate a situation where the power entity1140 exercises the option. Particularly, exercising the option maytrigger the load to reduce the amount of power it consumes by an amountup to 10 MW at any point during the 12 hour interval. By establishingthis power option agreement, the power entity 1140 can manipulate theamount of power consumed at the load during the next 12 hours by up to10 MW if power needs to be redirected to another load or a reduction inpower consumption is needed for other reasons.

In the example arrangement of the system 1100 shown in FIG. 11, one ormore of the datacenters (e.g., the flexible datacenters 1102, 1104, andthe traditional datacenter 1106) may operate as the load that is subjectto a power option agreement. As the load that is subject to the poweroption agreement, the datacenters 1102-1106 may execute controlinstructions in accordance with power target consumption targets thatmeet or exceed the minimum power thresholds based on the power optionagreement.

As shown in FIG. 11, each datacenter 1102-1106 may include a set ofcomputing systems configured to perform computational operations usingpower from one or more power sources (e.g., BTM power, grid power,and/or grid power subject to a power option agreement). In particular,the flexible datacenter 1102 includes computing systems 1108 arrangedinto a first set 1114A, a second set 1114B, and a third set 1114C, theflexible datacenter 1104 includes computing systems 1110 arranged into afirst set 1116A, a second set 1116B, and a third set 1118B, and thetraditional datacenter 1106 includes computing systems 1112 arrangedinto a first set 1118A, a second set 1118B, and a third set 1118C. Eachset of computing systems may include various types of computing systemsthat can operate in one or more modes.

The different sets of computing systems as well as the multipledatacenters are included in FIG. 11 for illustration purposes. Inparticular, the variety of computing systems represent differentconfigurations that a load may take while operating in accordance with apower option agreement, and each configuration (as detailed herein) mayinclude ramping up or down power consumption and transferring andperforming computational operations between sets of computing systemsand/or datacenters. In other examples, the load that is subject to apower option agreement may take on other configurations (e.g., a singledatacenter 1102-1106, and/or a single set of computing systems).

The remote master control system 262 may serve as a control system thatcan determine performance strategies and provide control instructions tothe load (e.g., one or more of the datacenters 1102-1106). Inparticular, the remote master control system 262 can monitor conditionsin concert with the minimum power thresholds and time intervals (e.g.,power option data) set forth in, and/or derived from, one or more poweroption agreements to determine performance strategies that can enablethe load to meet the expectations of the power option agreement(s) whilealso efficiently using power to accomplish computational operations. Insome instances, the remote master control system 262 may also be subjectto the power option agreement and may adjust its own power consumptionbased on the power option agreement (e.g., ramp up or down powerconsumption based on the defined minimum power thresholds during timeintervals).

To establish a power option agreement, the remote master control system262 (or another computing system) may communicate with the power entity1140. For instance, the remote master control system 262 may provide arequest (e.g., a signal and/or a bid) to the power entity 1140 andreceive the terms of one or more power option agreements, or poweroption data related to power option agreements (e.g., data such asminimum power thresholds and time intervals, but not all terms containedwithin a potential power option agreement) in response. In someexamples, the remote master control system 262 may evaluate one or moreconditions prior to establishing a power option agreement to ensure thatthe conditions could enable the load (e.g., the datacenters 1102-1106)to operate in accordance with the power option agreement. For instance,the remote master control system 262 may check the quantity anddeadlines associated with computational operations assigned to specificdatacenters prior to establishing specific datacenters as a load subjectto a power option agreement. In some cases, multiple power optionagreements may be established. For example, each datacenter 1102-1106may be subject to a different power option agreement, which may resultin the remote master control system 262 managing the power consumptionat each of the datacenters 1102-1106 differently.

Within the system 1100 shown in FIG. 11, the power entity 1140 mayrepresent any type of power entity associated with the delivery of powerto the load that is subject to a power option agreement. For instance,the power entity 1140 may be a local station control system, a gridoperator, or a power generation source. As such, the power entity 1140may establish power option agreements with the loads via communicationwith the loads and/or the remote master control system 262. For example,the power entity 1140 may obtain and accept a bid from a load trying toengage in a power option agreement with the power entity 1140. The powerentity 1140 is shown with a power option module 1142, which may be usedto establish power option agreements (e.g., fixed-duration 1144 and/ordynamic 1146).

Once a power option agreement is established, the remote master controlsystem 262 may obtain power option data from the power entity 1140 (oranother source) that specifies the power and time expectations of thepower entity 1140. As shown in FIG. 11, the power entity 1140 includes apower option module 1142, which may be used to provide power option datato the remote master control system 262 and/or the datacenters1102-1106. In particular, the power option data may specify the minimumpower threshold or thresholds associated with one or more time intervalsfor the load to operate at in accordance with based on the power optionagreement. The power option data may also specify other constraints thatthe load should operate in accordance with.

In some examples, the power option data may also include an indicationof a monetary penalty that would be imposed upon the load for failure tooperate as agreed upon for the power option agreement. In addition, thepower option data may also include an indication of a monetary benefitprovided to the load operating at power consumption levels that are inaccordance with a power option agreement. For instance, monetarybenefits could include reduced prices for power, credits for power,and/or monetary payments. In addition, the power option data may includefurther constraints upon power use, such as one or more maximum powerthresholds and corresponding time intervals for the maximum powerthresholds.

In some embodiments, the power entity 1140 may correspond to a qualifiedscheduling entity (QSE). A QSE may submit bids and offers on behalf ofresource entities (REs) or load serving entities (LSEs), such as retailelectric providers (REPs). QSEs may submit offers to sell and/or bids tobuy power (energy) in the Day-Ahead Market (e.g., the next 24 hours) andthe Real-Time Market. As such, the remote master control system 262 oranother computing system may communicate with one or more QSEs to engageand control one or more loads in accordance with one or more poweroption agreements.

In some examples, a power option agreement may take the form of a fixedduration power option agreement 1144. The fixed duration power optionagreement 1144 may specify a set of minimum power thresholds and a setof time intervals in advance for an upcoming fixed duration of timecovered by the agreement. Each minimum power threshold in the set ofminimum power thresholds may be associated with a time interval in theset of time intervals. Examples of such association are provided in FIG.12. The fixed duration power option agreement may be established inadvanced of the time period covered by the set of time intervals toenable the remote master control system 262 to prepare performancestrategies for the load (e.g., the datacenter(s)) associated with thepower option agreement. Thus, the remote master control system 262 mayevaluate the fixed duration power option and other monitored conditionsto determine performance strategies for a set of computing systems(e.g., one or more datacenters) during the different intervals thatsatisfy the minimum power thresholds.

In other examples, a power option agreement may take the form of adynamic power option agreement 1146. For a dynamic power optionagreement 1146, minimum power thresholds may be provided to the remotemaster control system 262 in real-time (or near real-time). Forinstance, a dynamic power option agreement may specify that the powerentity 1140 may provide adjustments to minimum power thresholds andcorresponding time intervals in real-time to the remote master controlsystem 262. For example, a dynamic power option agreement may providepower option data that specifies a minimum power threshold for immediateadjustments (e.g., for the next hour).

In an embodiment, a dynamic power option agreement 1146 may involverepeat communication between the remote master control system 262 andthe power entity 1140. Particularly, the power entity 1140 may providesignals to the remote master control system 262 that request powerconsumption adjustments to be initiated at one or more datacenters bythe remote master control system 262 over short time intervals, such asacross minutes or seconds. For example, the power entity 1140 maycommunicate to the remote master control system 262 to ramp powerconsumption down to a particular level within the next 5 minutes. As aresult, the remote master control system 262 may provide instructions toone or more datacenters to ramp down power consumption using a linearramp over the next 5 minutes to meet the particular level specified bythe power entity 1140. The remote master control system 262 may monitorthe linear ramp down of power consumption and increase or decrease therate that the datacenter(s) ramp down power use based on projections andupdates received from the power entity 1140. As a result, although theramp down of power consumption may initially be performed in a linearmanner to meet a power target threshold, the remote master controlsystem 262 may adjust the rate of power consumption decrease based onupdates from the power entity 1140. For example, 25 percent of theoverall power consumption ramp down may occur during a first period(e.g., 4 minutes 30 seconds) of the 5 minutes and the remaining 75percent of the overall power consumption ramp down may occur during theremaining period of the 5 minutes (e.g., the final 30 seconds). Theexample percentages are included for illustration purposes and can varywithin examples based on various parameters, such as additionalcommunication (e.g., adjustments) provided by the power entity 1140.

In further examples, a power option agreement may operate similarly toboth a fixed-duration 1144 and a dynamic power option agreement 1146.Particularly, power option data specifying minimum power thresholds andcorresponding time intervals may be provided in advance for the entirefixed-duration of time (e.g., the next 24 hours). Additional poweroption data may then be subsequently provided enabling the remote mastercontrol system 262 to make one or more adjustments to accommodate anychanges specified within the additional power option data. For instance,additional power option data may indicate that a power entity exercisedits option to deliver less power to the load. As a result, the remotemaster control system may instruct the load to adjust power consumptionbased on the power entity reducing the power threshold minimum viaexercising the option.

As indicated above, the remote master control system 262 may monitorconditions in addition to the constraints set forth in power option datareceived from the power entity 1140. Particularly, the remote mastercontrol system 262 may monitor and analyze a set of conditions(including the power option data) to determine strategies for assigning,transferring, and otherwise managing computational operations using theone or more datacenters 1102-1106. The determined strategies may enableefficient operation by the datacenters while also ensuring that thedatacenters operate at target power consumption levels that meet orexceed the minimum power thresholds set forth within one or more poweroption agreements.

Example monitored conditions include, but are not limited to, poweravailability 1120, power prices 1122, computing systems parameters 1124,cryptocurrency prices 1126, computational operation parameters 1128, andweather conditions 1129. Power availability 1120 may include determiningpower consumption ranges at a set of computing systems and/or at one ormore datacenters. In addition, power availability 1120 may also involvedetermining the source or sources of power available at a datacenter.For instance, the remote master control system 262 may identify thetypes of power sources (e.g., BTM, grid power, and/or a battery system)that a datacenter has available. Power prices 1122 may involve ananalysis of the different costs associated with powering a set ofcomputing systems. For instance, the remote master control system 262may determine cost of power from the grid without a power optionagreement relative to the cost power from the grid under the poweroption agreement. In addition, the remote master control system 262 mayalso compare the cost of grid power relative to the cost of BTM powerwhen available at a datacenter. The power prices 1122 may also involvecomparing the cost of using power at different datacenters to determinewhich datacenter may perform computational operations at a lower cost.

Monitoring computing system parameters 1124 may involve determiningparameters related to the computing systems at one or more datacenters.For instance, the remote master control system 262 may monitor variousparameters of the computing systems at a datacenter, such as theabilities and availability of various computing systems, the status ofthe queue used to store computational operations awaiting performance bythe computing systems. The remote master control system 262 maydetermine types and operation modes of the computing systems, includingwhich computing systems could operate in different modes (e.g., a higherpower or a lower power mode) and/or at different hash rates and/orfrequencies. The remote master control system 262 may also estimate whencomputing systems may complete current computational operations and/orhow many computational operations are assigned to computing systems.

Monitoring cryptocurrency prices 1126 may involve monitoring the currentprice of one or more cryptocurrencies, the hash rate and/or estimatedpower consumption associated with mining each cryptocurrency, and otherfactors associated with the cryptocurrencies. The remote master controlsystem 262 may use data related to monitoring cryptocurrency prices 1126to determine whether using computing systems to mine a cryptocurrencygenerates more revenue than the cost of power required for performanceof the mining operations.

The remote master control system 262 may monitor parameters related tocomputational operations (e.g., computational operation parameters1128). For example, the remote master control system 262 may monitorparameters related to the computational operations requiring performanceand currently being performed, such quantity of operations, estimatedtime to complete, cost to perform each computational operation,deadlines and priorities associated with each computational operation.In addition, the remote master control system 262 may analyzecomputational operations to determine if a particular type of computingsystem may perform the computational operation better than other typesof computing systems.

Monitoring weather conditions 1129 may include monitoring for anypotential power generation disruption due to emergencies or otherevents, and changes in temperatures or weather conditions at powergenerators or datacenters that could affect power generation. As such,the operations and environment analysis module (or another component) ofthe remote master control system 262 may be configured to monitor one ormore conditions described above.

The performance strategy determined by the remote master control system262 based on the monitored conditions and/or power option data caninclude control instructions for the load (e.g., the datacenters and/orone or more sets of computing systems). For instance, a performancestrategy can specify operating parameters, such as operatingfrequencies, power consumption targets, operating modes, power on/offand/or standby states, and other operation aspects for computing systemsat a datacenter.

The performance strategy can also involve aspects related to theassignment, transfer, and performance of computational operations at thecomputing systems. For instance, the performance strategy may specifycomputational operations to be performed at the computing systems, anorder for completing computational operations based on prioritiesassociated with the computational operations, and an identification ofwhich computing systems should perform which computational operations.In some instances, priorities may depend on revenue associated withcompleting each computational operation and deadlines for eachcomputational operation.

The monitored conditions may enable efficient distribution andperformance of computational operations among computing systems at oneor more datacenters (e.g., datacenters 1102-1106) in ways that canreduce costs and/or time to perform computational operations, takeadvantage of availability and abilities of computing systems at thedatacenters 1102-1106, and/or take advantage in changes in the cost forpower at the datacenters 1102-1106. In addition, the monitoredconditions may also involve consideration of the power option data toensure that the computing systems consume enough power to meet minimumpower thresholds set forth in one or more power option agreements.

The various monitored conditions described above as well as otherpotential conditions may change dynamically and with great frequency.Thus, to enable efficient distribution and performance of thecomputational operations at the datacenters, the remote master controlsystem 262 may be configured to monitor changes in the variousconditions to assist with the efficient management and operations of thecomputing systems at each datacenter. For instance, the remote mastercontrol system 262 may engage in wired or wireless communication 1130with datacenter control systems (e.g., datacenter control system 504) ateach datacenter as well as other sources (e.g., the power entity 1140)to monitor for changes in the conditions.

The remote master control system 262 may analyze the differentconditions in real-time to modulate operating attributes of computingsystems at one or more of the datacenters. By using the monitoredconditions, the remote master control system 262 may increase revenue,decrease costs, and/or increase performance of computational operationsvia various modifications, such as transferring computational operationsbetween datacenters or sets of computing systems within a datacenter andadjusting performance at one or more sets of computing systems (e.g.,switching to a low power mode).

In some examples, the traditional datacenter 1106 may be the loadsubject to a power option agreement. As such, the remote master controlsystem 262 may factor the power option agreement when determiningwhether to perform computational operations using the computing systems1112 at the traditional datacenter 1106 and/or transfer computationaloperations to the computing systems 1108, 1110 at the flexibledatacenters 1102, 1104. For instance, the monitored conditions mayindicate that the price of grid power is substantially higher than BTMpower. As a result, the remote master control system 262 may transfer asubset of computational operations from the traditional datacenter 1106to the flexible datacenters 1102, 1104. The traditional datacenter 1106may still have some computational operations to perform to ensure thatthe traditional datacenter 1106 is using enough power to meet theminimum power threshold or thresholds set forth in the power optionagreement.

In some examples, the remote master control system 262 may monitor thegrid frequency signal received from the power entity 1140. When thefrequency of the grid deviates a threshold amount (e.g., 0.036 Hz aboveor below 60 Hz), the remote master control system 262 may adjustperformance strategies at the load. In some cases, the remote mastercontrol system 262 may adjust the power consumption at the load, thenumber of miners (or computing systems) operating at the load, and/orthe frequency or hash rate, among other possible changes. The remotemaster control system may readjust performance strategies at the load inresponse to receiving additional power option data from the power entity1140 (e.g., an indication that the frequency of the grid is back to 60Hz). In addition, the remote master control system 262 may communicatechanges in operations at the load to the power entity 1140. This way,the power entity 1140 may obtain confirmation that the load is adjustingin accordance with a power option agreement.

In some embodiments, a power generation source (e.g., the generationstation 400 shown in FIG. 4) may enter into a power option agreementwith a grid operator, which may provide the grid operator with theoption to reduce the amount of power that the power source generator candeliver to the grid during a defined time interval. For instance, a windgeneration farm may enter into the power option agreement with the gridoperator. In addition, the remote master control system 262 may alsoenter into a power option agreement with the power generation source(e.g., the wind farm) to provide a load that can receive excess powerfrom the power generation source when the grid operator exercises theoption and lowers the amount of power that the power generation sourcecan deliver to the grid. Thus, rather than reducing the amount of powerproduced, the power generation source could exercise an option in theagreement with remote master control system 262 and redirect excesspower to one or more loads (e.g., a set of computing systems) that couldramp up power consumption in response. In such situations, the remotemaster control system 262 maybe able to use the excess power from thepower generation source (e.g., BTM power) to perform operations at oneor more loads at a low cost (or no cost at all). In addition, the powergeneration source may benefit from the power option agreement bydirecting excess power to the load instead of temporarily halting powerproduction.

In some examples, a power option agreement may depend on parametersassociated balancing grid capacity and demand. For instance, poweroption agreements may incentivize power consumption ramping duringperiods of peak grid power use.

FIG. 12 shows a graph representing power option data based on a poweroption agreement, according to one or more embodiments. The graph 1200shows power option data arranged according to power 1204 over time 1202.As shown in FIG. 12, time 1202 increases along the X-axis and minimumpower thresholds 1204 increase along the Y-axis of the graph 1200. Inthe example embodiment shown in FIG. 12, the time 1202 increases up to afull day (e.g., 24 hours) in 4 hour increments and the power is shown inMW increasing in intervals of 5 MW. The 24 duration and example minimumpower thresholds can differ in other embodiments. Particularly, thesevalues may depend on the terms set forth within the power optionagreement.

The graph line 1206 represents sets of minimum power thresholds 1206A,1206B, 1206C that are specified by power option data based on the poweroption agreement. As shown, the graph line 1206 extends the entire 24hour duration, which indicates that the set of time intervals associatedwith minimum power thresholds add up to 24 hours. In other examples, thepower option agreement may not include a minimum power threshold duringa portion of the duration.

The graph line 1206 of the graph 1200 is further used to illustratepower consumption levels that one or more loads (e.g., a set ofcomputing systems) operating according to the power option agreement mayutilize during the 24 hour duration. Particularly, the power quantitiesabove the graph line 1206 represents power levels that the load(s) mayconsume from the power grid during the 24 hour duration that wouldsatisfy the requirements (i.e., the minimum power thresholds1206A-1206C) set forth by the power option agreement. In particular, thepower quantities above the graph line 1206 include any power quantitythat meets or exceeds the minimum power threshold at that time. Byextension, the power quantities positioned below the graph line 1206represents the amount of power that the load could be directed to reducepower consumption by per the power option agreement.

To further illustrate, an initial minimum power threshold 1206A is shownassociated with the time interval starting at hour 0 and extending tohour 8. In particular, the minimum power threshold 1206A is set at 5 MWduring this time interval. Thus, based on the power option data shown inFIG. 12, the loads must be able to operate at a target power consumptionlevel that is equal to or greater than the 5 MW minimum power threshold1206A at all times during the time interval extending from hour 0 tohour 8, in order to be able to satisfy the power option if it isexercised for that time interval. Similarly, the power entity couldreduce the power consumed by loads by any amount up to 5 MW at any pointduring the time interval from hour 0 to hour 8 in accordance with thepower option agreement. For instance, the power entity could exerciseits option at any point during this time interval to reduce the powerconsumed by the loads by 3 MW as a way to load balance the power grid.In response to the power entity exercising its option, the load may thenoperate using 3 MW less power and/or another strategy determined by acontrol system factoring additional conditions (e.g., the price of gridpower, the revenue that could be generated from mining a cryptocurrency,and/or parameters associated with computational operations awaitingperformance)

As further shown in the graph 1200 illustrated in FIG. 12, the nextminimum power threshold 1206B is associated with the following timeinterval, which starts at hour 8 and extends until hour 16. During thistime interval (hour 8 to hour 16), the load(s) may consume 10 MW or morepower since the minimum power threshold 1206B is now set at 10 MW asshown on the Y-axis of the graph 1200. In light of the power optiondata, a control system may determine and provide a performance strategyto the load (e.g., a set of computing systems) that includes a powerconsumption target that meets or exceeds the minimum power threshold1206B (i.e., 10 MW). The performance strategy may depend on the poweroption data as well as other possible conditions, such as the price ofgrid power, the availability of computing systems, and/or the type ofcomputing operations, etc. In addition, the power entity could exerciseits option to reduce the amount of power consumed by the load by 10 MWor less as represented by the power levels under the minimum threshold1206B that extend during the time interval of hour 8 to hour 16.

The last minimum power threshold 1206C is associated with the timeinterval that starts at hour 16 and extends until hour 24. Similar tothe initial minimum power threshold 1206A associated with the beginningof the graph line 1206, the last minimum power threshold 1206 is alsoset at 5 MW. As such, at any point during this interval (hour 16 to hour24) the loads may consume 5 MW or more to operate in accordance with thepower option agreement. As discussed above, by operating at 5 MW ormore, the load enables the power consumed from the power grid to bereduced any amount from zero up to 5 MW during this time interval.

When determining the power consumption strategy for a load, a computingsystem (e.g., the remote master control system 262) may consider variousconditions in addition to the power option data received based on one ormore power option agreements. Particularly, the computing system mayconsider and weigh different conditions in addition to the power optiondata to determine power consumption targets and/or other controlinstructions for a load. The conditions may include, but are not limitedto, the price of grid power, the price of alternative power sources(e.g., BTM power, stored energy), the revenue associated with mining forone or more cryptocurrencies, parameters related to the computationaloperations requiring performance (e.g., priorities, deadlines, status ofthe queue organizing the operations, and/or revenue associated withcompleting each computational operation), parameters related to the setof computing systems (e.g., types and availabilities of computingsystems), and other conditions (e.g., penalties if a minimum powerthreshold is not met and/or monetary benefits from operating under apower option agreement). By weighing various conditions, the computingsystem may efficiently manage the set of computing systems, includingenabling performance of computational operations cost effectively and/orensuring at that computing systems operate at target power consumptionlevels that one or more satisfy power option agreements.

In some examples, the computing system may decrease the amount of powerthat a set of computing systems consumes from one source and while alsoincreasing the amount of power that the set consumes from anothersource. For instance, the computing system may determine that the priceof power grid power is above a threshold price that makes computationaloperations relatively expensive to perform using grid power. As aresult, the computing system may provide control instructions for thecomputing systems to consume power grid power that matches a minimumpower threshold specified by power option data. This may enable thecomputing systems to satisfy the power option agreement while alsoavoiding using pricey grid power beyond the minimum amount required perthe power option data. In addition, the computing system may instructsome computing systems to switch to a low power mode or temporarily stopuntil the price of power from the grid decreases. The computing systemmay instruct one or more computing systems to operate using power fromanother source (e.g., BTM power and/or stored energy from a batterysystem) and/or transfer one or more computational operations to anotherset of computing systems (e.g., a different datacenter).

When the power option agreement is a fixed duration power optionagreement, the computing system may receive an indication of all theminimum power thresholds 1206A-1206C and an indication of the associatedtime interval altogether and in advance of the duration associated withthe power option agreement. By providing all of the minimum powerthresholds 1206A-1206C and the time intervals in advance, the computingsystem may determine a performance strategy for the load that can extendacross the entire duration. Particularly, the computing system mayfactor the minimum power thresholds and associated time intervals aswell as other monitored conditions to determine the performance strategyfor the total duration. This can enable the computing system to acceptand assign computational operations to computing systems in advancewhile also using a performance strategy that meets the expectations of apower option agreement.

In some examples, the performance strategy determined by the computingsystem may include control instructions for the set of computing systemsto execute if a power option is exercised. For instance, the performancestrategy may specify different power consumption targets for thecomputing systems that depend on whether a power option is exercisedduring each time interval.

In some instances, the computing system may modify the performancestrategy when one or more conditions change enough to warrant amodification. For instance, the computing system may receive anindication of a change in a minimum power threshold (e.g., a decrease inthe minimum power threshold) and determine one or more modificationsbased on the new minimum power threshold and/or other conditions (e.g.,a change in the price of power).

In other examples, the power option agreement may be a dynamic poweroption agreement. Particularly, the load may be subject to a changingminimum power threshold that can vary during a predefined durationassociated with the power option agreement. For example, a dynamic poweroption agreement may specify that the load is subject to a minimum powerthreshold that may vary from 0 MW up to 5 MW during the next 24 hoursand the particular minimum threshold for each hour may depend on poweroption data received from the power entity during the prior hour. Thedynamic power option agreement may further specify the expected responsetime from the load. For instance, the power option agreement mayindicate that an indication of a new minimum power threshold will beprovided an hour prior to the start of the minimum power threshold. Thecomputing system, for example, may receive an indication at hour 7 aboutthe increase in the minimum power threshold 1206B starting at hour 8.The indication may (or may not) specify the total time intervalassociated with a new minimum power threshold. For instance, theindication received by the computing system may specify that the 10 MWminimum power threshold 1206B extends from hour 8 until hour 16. Inother instances, the power option data may indicate that the computingsystem should abide by the new minimum power threshold until receivingfurther power option data indicating a change to another new minimumpower threshold.

In some examples, the power option data may arrive at the computingsystem in an unknown order from the power entity with expectations ofswift power consumption adjustments by the load. As a result, the poweroption agreement may require fast ramping of the load to meet changes.Ramping may involve ramping up or down power consumption as well asramping operating techniques (e.g., adjusting frequency or operationmode).

In some embodiments, the type of power option power agreement may dependon the delivery and content of power option data provided to the load(or a control system controlling the load). For instance, a computingsystem may receive minimum power thresholds set across an entireduration associated with a power option agreement in advance when thepower option agreement is a fixed-duration power option agreement. Inother instances, the computing system may receive power option datadynamically and adjust operations in real-time (or near real-time). Forinstance, the computing system may receive a series of power option datathat each specifies minimum power threshold changes during the durationset forth in the dynamic power option agreement. To illustrate anexample, the computing system may receive power option data during hour1 that specifies the minimum power threshold for hour 2, power optiondata during hour 2 that specifies the minimum power threshold for hour3, and so on across the duration of the dynamic power option agreement.

In some examples, the minimum power threshold for a time interval may bezero during the duration of a power option agreement. As such, the loadmay use any amount of power from the power grid in accordance with thepower option agreement, including no power at all during this timeinterval. When the price for power is high during this time frame, theload may ramp down power usage to zero MW to avoid paying the high pricefor power while still being in compliance with the power optionagreement.

FIG. 13 illustrates a method for implementing control strategies basedon a fixed-duration power option agreement, according to one or moreembodiments. The method 1300 serves as an example and may include othersteps within other embodiments. A control system (e.g., the remotemaster control system 262) may be configured to perform one or moresteps of the method 1300. As such, the control system may take variousforms of a computing system, such as a mobile computing device, awearable computing device, a network of computing systems, etc.

At step 1302, the method 1300 involves monitoring a set of conditions.For instance, a computing system (e.g., a control system) may monitorvarious conditions that could impact the performance of operations atone or more loads, including the power consumption targets at the loads.The set of monitored conditions may include a variety of informationobtained from one or more external sources, such as one or moredatacenters, databases, power generation stations, or types of sources.

Some example conditions include, but are not limited to, the price ofgrid power, the price and availability of alternative power options(e.g. BTM power, and/or stored energy), parameters of the load (e.g.,ramping abilities, type of computing systems, operation modes, etc.),parameters of tasks to be performed using the power at the load (e.g.,types, deadlines, priorities, and/or revenue associated withcomputational operations), availability of other computing systems andtheir associated costs, and/or revenue associated with mining acryptocurrency. The computing system may monitor one or more of theseconditions as well as others.

At step 1304, the method 1300 involves receiving power option databased, at least in part, on a power option agreement. As discussedabove, the computing system (e.g., a remote master control system) mayengage in a power option agreement with a power entity. As a result, thecomputing system may control a load (e.g., a set of computing systems)in accordance with power thresholds and time intervals received from thepower entity based on the power option agreement.

In some examples, the power option data may specify a set of minimumpower thresholds and a set of time intervals. Each minimum powerthreshold in the set of minimum power thresholds may be associated witha time interval in the set of time intervals. To illustrate an example,the power option data may specify a first minimum power thresholdassociated with a first time interval and a second minimum powerthreshold associated with a second time interval, with the second timeinterval subsequent to the first time interval.

The set of time intervals may add up to the duration represented by thepower option agreement. For instance, the total duration of the set oftime intervals may correspond to a twenty-four hour period (e.g., thenext day). In other examples, the power option agreement may span acrossa different duration (e.g., 12 hours). In additional embodiments, thepower option data may specify other information, such as monetaryincentives associated with parameters of the power option agreementand/or one or more maximum power thresholds.

At step 1306, the method 1300 involves determining a performancestrategy for the set of computing systems based on a combination of atleast a portion of the power option data and at least one condition inthe set of conditions. The performance strategy may be determinedresponsive to receiving the power option data. In addition, theperformance strategy may include a power consumption target for the setof computing systems for each time interval in the set of timeintervals. In some examples, each power consumption target is equal toor greater than the minimum power threshold associated with each timeinterval.

As an example, the performance strategy may specify a first powerconsumption target for the set of computing systems for a first timeinterval such that the first power consumption target is equal to orgreater than a first minimum power threshold associated with the firsttime interval and a second power consumption target for the set for asecond time interval in a similar manner (i.e., the second powerconsumption target is equal to or greater than a second minimum powerthreshold).

In some examples, the performance strategy may include an sequence forthe set of computing systems to follow when performing computationaloperations. The sequence, for example, may be based on prioritiesassociated with the computational operations. In addition, theperformance strategy may include one or more power consumption targetsthat are greater than the minimum power thresholds when the price ofpower from the power grid is below a threshold price during the timeintervals associated with the minimum power thresholds.

The performance strategy may also involve transferring, delaying, oradjusting one or more computational operations performed at the set ofcomputing systems. In addition, the performance strategy may involveadjusting operations at the computing systems. For instance, one or morecomputing systems may switch modes (e.g., operate at a higher frequencyor switch to a low power mode).

In addition, the performance strategy may also specify power consumptiontargets for the set of computing systems to use if the power option isexercised during an interval. This way, the computing systems maycontinue to perform computational operations (or suspend performance)based on the power option being exercised.

At step 1308, the method 1300 involves providing instructions to the setof computing systems to perform one or more computational operationsbased on the performance strategy. For example, the set of computingsystems may operate according to the performance strategy to ensure thatthe minimum power thresholds are met during the defined time intervalsbased on the power option agreement.

Some examples may further involve receiving subsequent power option databased, at least in part, on the power option agreement. The subsequentpower option data may specify to decrease one or more minimum powerthresholds of the set of power thresholds. Responsive to receiving thesubsequent power option data, the performance strategy for the set ofcomputing systems may be modified based on a combination of at least aportion of the subsequent power option data and one or more conditionsof the monitored conditions. The modified performance strategy mayinclude one or more reduced power consumption targets for the set ofcomputing systems. The amount of the reduction in a power consumptiontarget may depend linearly with the amount that the correspondingminimum power threshold was reduced by. For instance, when a minimumpower threshold for a time interval is reduced from 10 MW to 5 MW, thepower consumption target for that time interval may be reduced from 10MW to 5 MW. Instructions may be provided to the set of computing systemsto perform computational operations based on the modified performancestrategy.

FIG. 14 illustrates a method for implementing control strategies basedon a dynamic power option agreement, according to one or moreembodiments. The method 1400 serves as an example and may include othersteps within other embodiments. Similar to the method 1400, a controlsystem (e.g., the remote master control system 262) may be configured toperform one or more steps of the method 1400. As such, the controlsystem may take various forms of a computing system, such as a mobilecomputing device, a wearable computing device, a network of computingsystems, etc.

At block 1402, the method 1400 involves monitoring a set of conditions.Similar to block 1302 of the method 1300, a computing system may monitorvarious conditions to determine instructions for controlling a set ofcomputing systems.

At block 1404, the method 1400 involves receiving first power optiondata based, at least in part, on a power option agreement whilemonitoring the set of conditions. The first power option data mayspecify a first minimum power threshold associated with a first timeinterval. For example, the first power option data may specify a minimumpower threshold of 10 MW for the next hour, which may start in an houror less.

The power option agreement may correspond to a dynamic power optionagreement in some examples. When managing a load with respect to adynamic power option agreement, a computing system may receive poweroption data specifying changes in minimum power thresholds that a load(e.g., the set of computing systems) may be designated to use in thenear term (e.g., the next hour). For example, the computing system mayreceive power option data during each hour of the duration specified bya power option agreement that indicates a minimum power threshold forthe next hour.

At block 1406, the method 1400 involves providing first controlinstructions for a set of computing systems based on a combination of atleast a portion of the first power option data and at least onecondition. The first control instructions may be provided responsive toreceiving the first power option data.

The first control instructions may include a first power consumptiontarget for the set of computing systems for the first time interval.Particularly, the first power consumption target may be equal to orgreater than the first minimum power threshold associated with the firsttime interval. For example, the first power consumption target may begreater than the first minimum power threshold when a cost of power fromthe power grid is below a threshold price during the first timeinterval. In other instances, the first power consumption target may beequal to the first minimum power threshold when the cost of power fromthe power grid is greater than the threshold price.

In some examples, control instructions may specify a sequence for thecomputing systems to follow when performing computational operations.The sequence may be based on priorities associated with eachcomputational operation.

The first control instructions may be determined based on a combinationof the first power option data, the price of power from the power grid,and parameters associated with computational operations to be performedat the set of computing systems.

In some examples, the first control instructions may involve ramping upor down power consumption at the set of computing systems. The powerconsumption may be ramped up or down based on the first minimum powerthreshold and one or more other conditions (e.g., the price of power).

At block 1408, the method 1400 involves receiving second power optiondata based, at least in part, on the power option agreement whilemonitoring the set of conditions. The computing system may receive thesecond power option data subsequent to receiving the first power optiondata. The second power option data may specify a second minimum powerthreshold associated with a second time interval. For example, thesecond minimum power threshold may be 7 MW over the duration of theupcoming hour. In other examples, the second minimum power threshold maydiffer as shown in FIG. 12.

In some instances, the computing system may receive the second poweroption data during the first time interval such that the second timeinterval overlaps the first time interval. For instance, the computingsystem may receive the second power option data to enable real-timeadjustments to be made to the power consumed at the set of computingsystems.

At block 1410, the method 1400 involves providing second controlinstructions for the set of computing systems based on a combination ofat least a portion of the second power option data and at least onecondition. The second control instructions may be provided responsive toreceiving the second power option data. The second control instructionsmay specify a second power consumption target for the set of computingsystems for the second time interval. The second power consumptiontarget may be equal to or greater than the second minimum powerthreshold associated with the second time interval.

In some examples, the computing system may provide a request to a QSE todetermine the power option agreement. As such, the computing system mayreceive power option data (e.g., the first and second power option data)in response to providing the request to the QSE.

The computing system may monitor the price of power from the power grid,and the global mining hash rate and a price for a cryptocurrency (e.g.,Bitcoin), among other conditions. The computing system may determinecontrol instructions (e.g., the first and/or second controlinstructions) based on a combination of power option data, the price ofpower from the power grid, and the global mining hash rate and the pricefor the cryptocurrency. For instance, the computing system may cause oneor more computing systems (e.g., a subset of computing systems) toperform mining operations for the cryptocurrency when the price of powerfrom the power grid is equal to or less than a revenue obtained byperforming the mining operations for the cryptocurrency.

Advantages of one or more embodiments of the present invention mayinclude one or more of the following:

One or more embodiments of the present invention provides a greensolution to two prominent problems: the exponential increase in powerrequired for growing blockchain operations and the unutilized andtypically wasted energy generated from renewable energy sources.

One or more embodiments of the present invention allows for the rapiddeployment of mobile datacenters to local stations. The mobiledatacenters may be deployed on site, near the source of powergeneration, and receive low cost or unutilized power behind-the-meterwhen it is available.

One or more embodiments of the present invention provide the use of aqueue system to organize computational operations and enable efficientdistribution of the computational operations across multipledatacenters.

One or more embodiments of the present invention enable datacenters toaccess and obtain computational operations organized by a queue system.

One or more embodiments of the present invention allows for the powerdelivery to the datacenter to be modulated based on conditions or anoperational directive received from the local station or the gridoperator.

One or more embodiments of the present invention may dynamically adjustpower consumption by ramping-up, ramping-down, or adjusting the powerconsumption of one or more computing systems within the flexibledatacenter.

One or more embodiments of the present invention may be powered bybehind-the-meter power that is free from transmission and distributioncosts. As such, the flexible datacenter may perform computationaloperations, such as distributed computing processes, with little to noenergy cost.

One or more embodiments of the present invention provides a number ofbenefits to the hosting local station. The local station may use theflexible datacenter to adjust a load, provide a power factor correction,to offload power, or operate in a manner that invokes a production taxcredit and/or generates incremental revenue.

One or more embodiments of the present invention allows for continuedshunting of behind-the-meter power into a storage solution when aflexible datacenter cannot fully utilize excess generatedbehind-the-meter power.

One or more embodiments of the present invention allows for continueduse of stored behind-the-meter power when a flexible datacenter can beoperational but there is not an excess of generated behind-the-meterpower.

One or more embodiments of the present invention allows for managementand distribution of computational operations at computing systems acrossa fleet of datacenters such that the performance of the computationaloperations take advantages of increased efficiency and decreased costs.

It will also be recognized by the skilled worker that, in addition toimproved efficiencies in controlling power delivery from intermittentgeneration sources, such as wind farms and solar panel arrays, toregulated power grids, the invention provides more economicallyefficient control and stability of such power grids in theimplementation of the technical features as set forth herein.

While the present invention has been described with respect to theabove-noted embodiments, those skilled in the art, having the benefit ofthis disclosure, will recognize that other embodiments may be devisedthat are within the scope of the invention as disclosed herein.Accordingly, the scope of the invention should be limited only by theappended claims.

1. A system comprising: a set of computing systems coupled to abehind-the-meter (BTM) power generation source, wherein the set ofcomputing systems is configured to perform computational operations; acontrol system configured to: monitor a set of conditions; receive poweroption data that specify: (i) a set of minimum power thresholds, and(ii) a set of time intervals, wherein each minimum power threshold inthe set of minimum power thresholds is associated with a time intervalin the set of time intervals; responsive to receiving the power optiondata, determine a performance strategy for the set of computing systemsbased on a combination of at least a portion of the power option dataand at least one condition from the set of conditions, wherein theperformance strategy comprises a power consumption target for the set ofcomputing systems for each time interval in the set of time intervals,wherein each power consumption target is equal to or greater than theminimum power threshold associated with each time interval; and provideinstructions to the set of computing systems to perform one or morecomputational operations based on the performance strategy.
 2. Thesystem of claim 1, wherein the control system is configured to monitorthe set of conditions comprising: a price of power from a power grid;and a plurality of parameters associated with one or more computationaloperations to be performed at the set of computing systems.
 3. Thesystem of claim 2, wherein the control system is configured to:determine the performance strategy for the set of computing systemsbased on a combination of at least the portion option data, the price ofpower from the power grid, and the plurality of parameters associatedwith the one or more computational operations.
 4. The system of claim 3,wherein the performance strategy further comprises: an order for the setof computing systems to follow when performing the one or morecomputational operations, wherein the order is based on respectivepriorities associated with the one or more computational operations. 5.The system of claim 4, wherein the performance strategy furthercomprises: at least one power consumption target that is greater than aminimum power threshold when the price of power from the power grid isbelow a threshold price during the time interval associated with theminimum power threshold.
 6. The system of claim 1, wherein the controlsystem is further configured to: receive subsequent power option data,wherein the subsequent power option data specify to decrease one or moreminimum power thresholds of the set of minimum power thresholds.
 7. Thesystem of claim 6, wherein the control system is further configured to:responsive to receiving the subsequent power option data, modify theperformance strategy for the set of computing systems based on acombination of at least the portion of the subsequent power option dataand at least one condition in the set of conditions, wherein themodified performance strategy comprises one or more reduced powerconsumption targets for the set of computing systems.
 8. The system ofclaim 7, wherein the control system is further configured to: provideinstructions to the set of computing systems to perform the one or morecomputational operations based on the modified performance strategy. 9.The system of claim 1, wherein the control system is a remote mastercontrol system positioned remotely from the set of computing systems.10. The system of claim 1, wherein the control system is a mobilecomputing device.
 11. The system of claim 1, wherein the control systemis configured to receive the power option data while monitoring the setof conditions.
 12. The system of claim 1, wherein the control system isfurther configured to: provide a request to a qualified schedulingentity (QSE) to determine a power option agreement having power optiondata; and receive power option data in response to providing the requestto the QSE.
 13. The system of claim 1, wherein the power option dataspecify: (i) a first minimum power threshold associated with a firsttime interval in the set of time intervals, and (ii) a second minimumpower threshold associated with a second time interval in the set oftime intervals, wherein the second time interval is subsequent to thefirst time interval.
 14. The system of claim 13, wherein the controlsystem is configured to: determine the performance strategy for the setof computing systems such that the performance strategy comprises: afirst power consumption target for the set of computing systems for thefirst time interval, wherein the first power consumption target is equalto or greater than the first minimum power threshold; and a second powerconsumption target for the set of computing systems for the second timeinterval, wherein the second power consumption target is equal to orgreater than the second minimum power threshold.
 15. The system of claim1, wherein a total duration of the set of time intervals corresponds toa twenty-four hour period.
 16. The system of claim 1, wherein the set ofconditions monitored by the control system further comprise: a price ofpower from a power grid; and a global mining hash rate and a price for acryptocurrency; and wherein the control system is configured to:determine the performance strategy for the set of computing systemsbased on a combination of at the portion of the power option data, theprice of power from the power grid, the global mining hash rate and theprice for the cryptocurrency, wherein the performance strategy specifiesfor at least a subset of the set of computing systems to perform miningoperations for the cryptocurrency when the price of power from the powergrid is equal to or less than a revenue obtained by performing themining operations for the cryptocurrency.
 17. A method comprising:monitoring, by a computing system, a set of conditions; receiving, atthe computing system, power option data, wherein the power option dataspecify: (i) a set of minimum power thresholds, and (ii) a set of timeintervals, wherein each minimum power threshold in the set of minimumpower thresholds is associated with a time interval in the set of timeintervals; responsive to receiving the power option data, determining aperformance strategy for a set of computing systems based on acombination of at least a portion of the power option data and at leastone condition in the set of conditions, wherein the performance strategycomprises a power consumption target for the set of computing systemsfor each time interval in the set of time intervals, wherein each powerconsumption target is equal to or greater than the minimum powerthreshold associated with each time interval, and wherein the set ofcomputing systems is coupled to a behind-the-meter (BTM) powergeneration source; and providing instructions to the set of computingsystems to perform one or more computational operations based on theperformance strategy.
 18. The method of claim 17, wherein determiningthe performance strategy for the set of computing systems comprises:identifying information about the set of computing systems; anddetermining the performance strategy to further comprise instructionsfor at least a subset of the set of computing systems to operate at anincreased frequency based on a combination of at least the portion ofthe power option data and the information about the set of computingsystems.
 19. The method of claim 17, further comprising: receivingsubsequent power option data, wherein the subsequent power option dataspecify to decrease one or more minimum power thresholds of the set ofminimum power thresholds; responsive to receiving the subsequent poweroption data, modifying the performance strategy for the set of computingsystems based on a combination of at least the portion of the subsequentpower option data and at least one condition in the set of conditions,wherein the modified performance strategy comprises one or more reducedpower consumption targets for the set of computing systems; andproviding instructions to the set of computing systems to perform theone or more computational operations based on the modified performancestrategy.
 20. A non-transitory computer readable medium having storedtherein instructions executable by one or more processors to cause acomputing system to perform functions comprising: monitoring a set ofconditions; receiving power option data that specify: (i) a set ofminimum power thresholds, and (ii) a set of time intervals, wherein eachminimum power threshold in the set of minimum power thresholds isassociated with a time interval in the set of time intervals; responsiveto receiving the power option data, determining a performance strategyfor a set of computing systems based on a combination of at least aportion of the power option data and at least one condition in the setof conditions, wherein the performance strategy comprises a powerconsumption target for the set of computing systems for each timeinterval in the set of time intervals, wherein each power consumptiontarget is equal to or greater than the minimum power thresholdassociated with each time interval; and providing instructions to theset of computing systems to perform one or more computational operationsbased on the performance strategy.